Continuously updated data processing system and method for measuring and reporting on value creation performance that supports real-time benchmarking

ABSTRACT

The invention affords a data processing system and method for assessing the performance of a business enterprise in creating and realizing value. More particularly, the invention affords a data processing system and method that supports the provision of real-time benchmarking through a network of benchmarking service providers.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of U.S. application Ser.No. 10/173,904, filed Jun. 17, 2002, and entitled “Continuously UpdatedData Processing System and Method for Measuring and Reporting on ValueCreation Performance that Supports Real-Time Benchmarking”, which is acontinuation-in-part application of U.S. application Ser. No.09/809,544, filed Mar. 14, 2001, and entitled “Continuously Updated DataProcessing System and Method for Measuring and Reporting on ValueCreation Performance that Supports Real-Time Benchmarking,” which is acontinuation-in-part application of U.S. application Ser. No.09/809,502, filed Mar. 14, 2001, and entitled “Data Processing Systemand Method for Analysis of Financial and Non-financial Value Creationand Value Realization Performance of a Business Enterprise forProvisioning of Real-time Assurance Reports” and of U.S. Application ofU.S. application Ser. No. 09/809,758, filed Mar. 14, 2001, entitled“Data Processing System and Method for Analysis of Financial andNon-financial Value Creation and Value Realization Performance of aBusiness Enterprise”, which are continuation-in-part applications ofU.S. application Ser. No. 09/586,722, filed Jun. 5, 2000, entitled “DataProcessing System and Method for Analysis of Financial and Non-financialValue Creation Performance of a Business Enterprise” and of U.S.application Ser. No. 09/587,646, filed Jun. 5, 2000, entitled “DataProcessing System and Method that Provides an Integrated andComprehensive User Interface for Analysis of Value Creation Performanceof a Business Enterprise” which are respective continuation-in-partapplications of U.S. application Ser. No. 09/574,569, filed May 17,2000, entitled, “Continuously Updated Data Processing System forMeasuring Financial Value Creation”. All of the above-referencedapplications are fully and completely incorporated herein by reference.

BACKGROUND OF THE INVENTION

The present invention relates to a data processing system that measuresperformance in creating and realizing value by a business enterprisebased on past and anticipated future events. More particularly, thepresent invention relates to a data processing system and method thatsupports the provision of real time benchmarking through a network ofbenchmarking service providers.

A fundamental principle of traditional accounting and financialreporting methods is that the performance of a business enterprise isderived from transactions between the enterprise and other parties, suchas customers, suppliers and employees. Consequently, traditionalaccounting can be characterized as measuring value realized through suchtransactions. Traditional accounting systems can thus be characterizedas transaction-based.

This arrangement proved to be satisfactory through what can becharacterized as the manufacturing era. In today's world, however, themost important assets of many enterprises are not plant and equipmentbut rather knowledge, ideas, and skills. For the most part,knowledge-based assets are not acquired through third-partytransactions, but are rather developed in-house. As such, they are notadequately captured by traditional accounting methods.

As a result of these shortcomings of traditional accounting with respectto knowledge intensive companies, it is apparent that capital marketsare missing important information needed to rationally assess theperformance of a business enterprise. It has been argued thattraditional accounting methods are a declining predictor of stock pricesand produce largely irrelevant reports for companies with long researchand development pipelines. Without adequate accounting forknowledge-intensive enterprises, capital markets will performsub-optimal resource allocation.

Many recent developments have taken place in the field of accounting andfinancial reporting though none fully addresses these problems. Theseinclude: Economic Value Added (EVA); Balanced Scorecard, IntellectualCapital Management (ICM), Economic Resource Planning (ERP); and theGlobal Reporting Initiative (GRI). An attempt has been made to mitigatesome of traditional accounting's shortcomings with management'sdiscussion and analysis (MD&A) sections in annual reports, but MD&Adisclosure is itself in bad condition, with no clear standards,methodology, or reporting principles. Capital markets are not routinelysupplied with information that would permit monitoring of strategyimplementation, value creation, and risk management.

Thus, with the increased time-lag often found between value creation andvalue realization, an accounting model that focuses only on the latteris increasingly irrelevant for intensively knowledge-basedenterprises—and, indeed, enterprises in general are increasinglyknowledge-based. Traditional financial statements have simply notprovided sufficient information about knowledge assets.

When value creation was closely followed by value realization (the mousetrap was manufactured in March and sold in April) concentrating on justvalue realization alone was good enough. It is no longer good enoughtoday. A bio-pharmaceutical research company may spend research anddevelopment funds on a potential drug discovery for ten years beforesuccessful commercialization and revenue streams commence. The growingdeficits resulting from research and development write-offs displayed bytraditional accounting during those ten years do not convey timely andrelevant information. It is not that traditional accounting methodsfocussed on value realization should be abandoned. They are important,but they are not sufficient.

An additional drawback to traditional transaction-based accountingtechniques is that they tend to rely on summarization of transactionaldata on a monthly, quarterly, or annual basis in order to provideperiodic financial statements and reports. However, what is needed intoday's fast-paced environment is a method of providing continuouslyupdated information on value creation and realization.

An additional drawback to traditional accounting techniques is that theytend to capture only one dimension of value: namely, financial value.However, financial value is not the only dimension of value that isrelevant to understanding enterprise performance. For example,non-financial factors, such as avoiding harm to the natural environment,or contributing to a healthier community, may not yield direct financialbenefits to the enterprise in the short-run, but may be as important instrategic terms as increasing the financial returns to shareholders.

A further drawback to traditional accounting techniques is that theytend to measure performance from the perspective of only onestakeholder: that is, shareholders. However, in the modern economy,achieving a full understanding of enterprise performance requiresknowledge of the extent to which the enterprise is meeting theexpectations of other stakeholders, such as customers, employees,suppliers, business partners, and the communities and society withinwhich the enterprise operates.

Therefore, what is needed, by contrast to conventional techniques, is atechnique for providing value creation information for a businessenterprise from the perspectives of a variety of stakeholders, not justshareholders. What is further needed is a method of providing anintegrated perspective on both financial and non-financial valuecreation. What is also needed is a technique for providing measurementsof the performance of a business enterprise in creating value based uponprojections of future events and related benefits that result from suchevents. It is to these ends that the present invention is directed.

In addition, there is a need for a technique for providing continuouslyupdated measurements of the performance of a business enterprise increating and realizing value based on past and future events, andrelated benefits that will result from such events.

Such an event-based system should be organized on fundamentallydifferent principles than today's transaction-based accounting systems.This creates the prospect that an enterprise that wishes to track valuecreation performance, as well as traditional value realizationperformance, would need to maintain two entirely different systems: anevent-based value creation performance measurement and reporting system,and a transaction-based value realization accounting system. Maintainingtwo separate systems can be inefficient and costly.

Thus, a method of adapting a continuously updated event-based system sothat it is capable of producing traditional accounting reports andfinancial statements, in addition to measuring and reporting on valuecreation performance is needed.

Another drawback of traditional accounting is that it provides a generalpurpose set of value realization financial statements for a particularperiod of time, in a single format, as specified by Generally AcceptedAccounting Principles (GAAP). There is thus a need for astakeholder-user to be able to select the attributes of a particularoutcome display that is updated in real-time.

An important feature of traditional value realization accounting hasbeen the development of standards and procedures that enable anindependent third party auditor or independent internal auditor toprovide assurance to users of financial statements. Provision ofassurance in this way enhances the credibility of financial information,and is an important element in the proper functioning of capitalmarkets.

Assurance has traditionally been provided in the form of a standardizedaudit report, whereby an assurance provider attests to the accuracy offinancial or non-financial information based on evidence obtainedthrough an audit conducted in accordance with generally-acceptedauditing standards. In the past, it was not necessary to customize anassurance report to the needs of a particular user, since traditionally,audit reports were usually provided on financial statements prepared ina standardized format.

For information produced by a continuously updated data processingsystem for measuring and reporting on value creation and valuerealization to be of maximum utility to stakeholders, it is desirable toprovide methods by which assurance can be provided by third party orindependent internal auditors.

There are significant differences between a traditional financialaccounting system and a continuously updated data processing system formeasuring and reporting on value creation and value realization thathave major implications for assurance providers. For example, it isdesirable in a continuously updated data processing system for measuringand reporting on value creation and value realization that assuranceprocedures be automated so that they can be undertaken in real time, inparallel with the generation of the outcome displays on which assuranceis being provided. It is also desirable that, where appropriate,stakeholder-users be able to specify the level of assurance theyrequire, and that assurance reports be customized in order to berelevant to the particular outcome display to which they refer, takinginto account the choices made by a stakeholder-user in selecting theattributes of a particular outcome display. It is also desirable thatcertain real time automated procedures and the generation of anassurance report in real-time be performed independently by the thirdparty assurance provider on a parallel system.

In providing continuously updated information on value creationperformance, one of the needs of business enterprises is to benchmarktheir performance against other comparative companies. It is desirableto provide benchmarking information on value creation performance inreal-time, in a manner that enables comparisons to be made withcomparable firms, functions or data in a manner that protects theconfidentiality of enterprise information. It is to these and other endsthat the present invention is directed.

SUMMARY OF THE INVENTION

The invention affords a data processing system and method for assessingthe performance of a business enterprise in creating and realizingvalue. More particularly, the invention affords a data processing systemand method that supports the provision of real-time benchmarking througha network of benchmarking service providers.

The system provides a stakeholder-user with up-to-the-minute valuecreation information regarding the business enterprise.Stakeholder-users may also review underlying assumptions, makealterations to the assumptions and see the results of value creationanalysis based on those altered assumptions. In addition,stakeholder-users may contribute performance-related informationreflecting their own experience with the enterprise for incorporationinto the data regarding the value creation performance of theenterprise.

The system further provides reports (outcome displays) on value creationperformance of the enterprise tailored for each of the key stakeholdergroups of the enterprise.

The system addresses shortcomings of conventional financial accountingtechniques by measuring and reporting future value streams, not justhistorical transactions, measuring and reporting value streams for allkey stakeholders, including both financial and non-financial value; andmeasuring and reporting value creation on a continuous, real-time basis.

In shifting the focus from shareholders to a broader set ofstakeholders, information may be obtained to evaluate value creationperformance from the perspective of the stakeholder groups. Theinvention addresses this by providing two types of stakeholderinteractivity. First, the system may provide an opportunity forstakeholders to input data regarding corporate performance as they haveexperienced it from a customer, employee, or other stakeholderperspective. Secondly, the stakeholders may interact with the system,thus enabling them to select the information that is most relevant tothem.

The system further provides continuously updated outcome displays onvalue realization performance similar to outcome displays that wouldotherwise be available from a transaction-based accounting system.

In an aspect, the invention affords a method for providing real-timebenchmarking information relating to the performance of a businessenterprise comprising the steps of developing a data structure includinginformation related to the performance of a business enterprise;initiating a request for benchmarking information to a benchmarkingnetwork including one or more benchmarking service providers, each ofthe benchmarking service providers having one or more associatedclients, the benchmarking service providers relaying the request forbenchmarking information to their clients; responding to the request forbenchmarking information by providing relevant benchmarking informationto the associated benchmarking service providers; and aggregating thereceived benchmarking information to yield composite benchmarkinformation relating to the performance of the business entity.

The data structure may include information relating to the valuecreation performance of a business enterprise, information relating tothe value realization performance of a business enterprise, orinformation relating to the performance of a business enterprise asmeasured by generally accepted alternative performance reportingformats. Further, the data structure includes a plurality of future andpast events and related assumptions. The benchmarking request may berepeatedly generated based on the occurrence of one or more events.Alternatively, accumulation of benchmarking information may take placecontinuously in the background.

In features of the invention, the initiating step further comprisesinitiating a request for benchmarking information to a firstbenchmarking service provider, and relaying that request to the one ormore additional benchmarking service providers in the benchmarkingnetwork. For each notified client, the responding step further comprisessearching for relevant benchmarking information from associated datastructures and providing the relevant benchmarking information to theassociated benchmarking service providers. Further, the aggregating stepfurther comprises firstly aggregating by each of the associatedbenchmarking service providers the relevant benchmarking informationfrom each of the responding client systems, providing the aggregatedbenchmarking information to the first benchmarking service provider, andsecondly aggregating the aggregated benchmarking information with therelevant benchmarking information provided to the first benchmarkingservice provider from its client systems. In addition, benchmarkingservice providers may agree to continuously pool commonly requestedbenchmarking information in order to speed the response time of thesystem in response to benchmarking requests.

In another aspect, the invention affords a system for providingreal-time benchmarking information relating to the performance of abusiness enterprise. The system comprises a memory device for storing adata structure including a plurality of first assumed variables thathave an influence on a non-financial value stream of the businessenterprise and including a plurality of second assumed variables thathave an influence on a financial value stream of the businessenterprise, a calculation engine for determining a first outcome of thenon-financial value stream of the business enterprise based upon eventscharacterized by the first assumed variables, the first outcomeinfluencing at least one of the second assumed variables and fordetermining a first present value of the financial value stream of thebusiness enterprise based upon the first outcome and based upon thesecond assumed variables, an outcome display module for selectingoutcome display reporting parameters for generating reports frominformation stored in the memory device, the outcome display reportingparameters being associated with certain ones of the first and secondassumed variables stored in the memory device, a filter coupled with thecalculation engine for selecting those certain ones of the first andsecond assumed variables from the memory device to be delivered to thecalculation engine, and a benchmarking module for providing benchmarkinginformation relating to the comparable performance of a particularbusiness enterprise with other business enterprises.

In features of the invention, present and future events arecharacterized by the first and second assumed variables. In addition,the calculation engine repeatedly determines a series of updatedoutcomes of the non-financial value stream of the business enterpriseand a series of updated present values of the financial value stream ofthe business enterprise based upon any assumed variables in the datastructure including any assumed variables that have changed in responseto the occurrence or non-occurrence of one or more events. Thebenchmarking information is preferably provided in real-time and iscontinuously updated based upon any assumed variables in the datastructure being changed in response to the occurrence or non-occurrenceof one or more events.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates a block diagrammatic view of a computer networksystem in accordance with the present invention;

FIG. 1B illustrates a diagrammatic view of initial choices that may beavailable to a user in determining whether to view value creation orvalue realization information when using the system of the invention;

FIG. 2 illustrates a block diagrammatic view of software architecturefor enabling the value creation mode of the computer system of FIG. 1Ain accordance with the present invention;

FIG. 3 illustrates a flow diagram showing determination of outcomesbased upon different assumptions;

FIG. 4 illustrates a flow diagram for determining net present value offuture financial values streams of a business enterprise in accordancewith the present invention;

FIG. 5 illustrates the flow diagram of FIG. 4 including exemplaryprojected cash flows and related probabilities;

FIG. 6 illustrates the flow diagram of FIG. 3 including exemplary valuesfor various assumptions;

FIG. 7 illustrates a chart showing a comparison between targeted andactual values for on-time performance, a non-financial outcome;

FIG. 8 illustrates a chart showing a comparison between targeted andactual values for annual IP filings, another non-financial outcome;

FIG. 9 illustrates a chart showing a comparison between targeted andactual values for supercomputing capacity, yet another non-financialoutcome;

FIG. 10 illustrates a chart showing a comparison between targeted andactual numbers of extranets, a further non-financial outcome;

FIG. 11 illustrates an event matrix data structure for storingassumptions and their related events in accordance with the presentinvention when operating in value creation mode;

FIG. 12 illustrates the event matrix data structure of FIG. 11 includingexemplary assumptions and related events;

FIG. 13 illustrates an event matrix data structure for storing eventsand their related assumptions in accordance with the present inventionwhen operating in value creation mode;

FIG. 14 illustrates a flow diagram for determining the effect on presentvalue based on value destruction and its related probability inaccordance with the present invention;

FIG. 15 illustrates the flow diagram of FIG. 14 including an exemplaryvalue destruction and related probability;

FIG. 16 illustrates a flow diagram for determining an outcome variancefor different future scenarios in accordance with the present invention;

FIG. 17 illustrates an exemplary determination of outcome variance;

FIG. 18 illustrates a flow diagram for operation of the computer systemof FIG. 1A including various modes of user interaction in accordancewith the present invention;

FIG. 19 illustrates an exemplary arrangement of data in the event matrixin which user identities are stored in association with assumptions;

FIG. 20 illustrates groupings of information from the matrix 400 whichwas provided by various stakeholders;

FIG. 21 illustrates various metrics for which feedback may be providedby users or stakeholders in accordance with the present invention;

FIG. 22 illustrates an event/assumption filter and calculation enginefor determining various different outcomes based on the storedassumptions of various users;

FIG. 23 illustrates a block diagrammatic view of a software architecturefor enabling the system of the invention to operate in value realizationmode;

FIG. 24 is a diagrammatic view of the event matrix module of FIG. 23illustrating an example of certain event attributes for storing eventinformation that may be used by the system while operating in valuerealization mode;

FIG. 25A is a diagrammatic view of a customer object record that may bestored in the object database;

FIG. 25B is a diagrammatic view of a product object record that may bestored in the object database;

FIG. 25C is a diagrammatic view of a financial object record that may bestored in the object database;

FIG. 26 is a diagrammatic view illustrating interaction between theevent matrix module and the object database module for generating valuerealization outcome displays in accordance with the invention;

FIG. 27 is a diagram illustrating a process flow for generating valuerealization outcome displays in accordance with the invention;

FIG. 28 illustrates an example of outcome display generation using anoutcome display interface for formatting customized outcome displaysbased on choices made by a stakeholder-user using the invention;

FIG. 29 is a flow chart illustrating an exemplary method by which acustomized assurance report on an outcome display may be generated inreal time based on various automated procedures in accordance with theinvention;

FIGS. 30A and 30B illustrate an exemplary representation of assuranceprocedure decision rules that may be used by the system to generate acustomized assurance report;

FIGS. 31A, 31B, and 31C illustrate an exemplary representation of theresults of applying particular assurance procedure decision rules togenerate a customized assurance report in accordance with the invention;and

FIG. 32 is a flow chart illustrating a method for providing real-timebenchmarking information relating to the performance of a businessentity in accordance with the invention.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT

FIG. 1A illustrates a block diagrammatic view of a computer networksystem 100 in accordance with the present invention. The system 100 mayinclude a central processing unit (CPU) 102, a database 104, a display106, a keyboard and mouse 108, a printer 110 and may interface withremote systems via a wide area network (WAN) or extranet 112 and localarea network (LAN) or intranet 114. Printed outcome displays 116 may beprovided by the printer 110.

Users may access the system 100 directly using the keyboard 108 andmonitor 106, or remotely over the LAN or intranet 114, the WAN orextranet 112, or the World Wide Web. Results can be displayed on thelocal monitor 106, or printed by the local printer 110. Alternately, theresults can be displayed by a remote computer monitor or printer (notshown).

It will be apparent that the computer network system 100 is conventionaland that various modifications or substitutions may be made. The system100 may embody the present invention by configuring the CPU 102 tooperate in accordance with stored software programs so as to interactwith data stored in the database 104, as explained herein.

Data that is relevant to performance of a business enterprise maymaintained in the database 104 (FIG. 1A). As used herein, “businessenterprise” is intended to encompass for profit, not-for-profit andgovernmental organizations. The database 104 may be in form of arelational database. Input and output from the database 104 may be inthe context of value creation or value realization.

The value creation context permits selection of one of four different“perspectives” into the data (e.g., each perspective may be anorganization or arrangement of the data). These perspectives mayinclude: a perspective that reflects the company's strategy for creatingand realizing value, referred to herein as the value creation andrealization formula; a value stream model perspective; a value creationcapacity perspective; and a value creation for multiple stakeholdersperspective.

The value creation and realization formula perspective provides asuccinct overview of the business enterprise's strategy for creating andrealizing value. This can include, for example, an identification of thegoods or services to be provided by the business, an identification ofthe enterprise's position in any related value chain, an identificationof the enterprise's strategy with respect to alliances, anidentification of the enterprise's approach to financing its present andfuture operations, an identification of likely consumers of the goods orservices, an identification of various markets to be entered and a timeschedule in which those markets are anticipated to be entered. Thus, thedatabase 104 may store such parameters in a matrix referred to herein asthe formula matrix.

The value stream model perspective is described in more detail hereinand relates to performance measurement of the business enterprise withrespect to future value creation. This may include, for example, storingmeasurements of present financial value of one or more value streams ofthe business enterprise based upon projections of future events,including assumptions regarding the future events, probabilities oftheir occurrence and monetary amounts expected to be realized shouldthey occur.

For the purposes of this document, a “value stream” for a businessenterprise is an aggregation of financial and non-financial benefitsflowing to the business and arising from a minimum set of activitiesthat are necessary to give rise to the benefits. A “future value stream”refers to those benefits which have not yet occurred with respect to aparticular point in time, such as the present. An “historical valuestream” refers to those benefits that have already been realized withrespect to a particular point in time. A “financial value stream” refersto those benefits that are reducible to cash or cash equivalents. A“non-financial value stream” refers to those benefits that are notreadily reducible to cash or cash equivalents. For example, anon-financial benefit may be enhanced customer loyalty. In addition tobenefits, a value stream may have associated costs, such as cashoutflows.

Events give rise to the benefits associated with value streams. Anhistorical event may give rise to a benefit that has already beenrealized with respect to a particular point in time. For example, a saleof goods in the past (an historical event) may have already resulted ina financial benefit to the seller of the goods, in which case, thebenefit belongs to an historical value stream. In addition, historicalevents may result in a benefit that has yet to be realized. For example,a license agreement already entered into (an historical event) mayresult in periodic payments that are not yet payable with respect to aparticular point in time, in which case, these benefits are part of afuture value stream. A series of related events are referred to hereinas an “event stream.” The database 104 may store parameters relating toevents, benefits and value streams in a matrix referred to herein as theevent matrix.

The value creation capacity perspective relates to the capabilities,infrastructure and networks required by the business enterprise forcarrying out its strategy for creating and realizing value. Valuecreation capabilities may include, for example, manufacturing capabilityand innovation capability. The value creation infrastructure mayinclude, for example, office space and capital equipment, such astelephone and computer systems. Value creation networks may include, forexample, relationships with other business enterprises, such assuppliers, customers and distributors. Thus, the database 104 may storesuch parameters in a matrix referred to herein as the capacity matrix.

The value creation for multiple stakeholders' perspective relates tomeasurement of financial and non-financial value creation for keystakeholders. For example, a key stakeholder may be a shareholder in thebusiness enterprise, in which case, the shareholder may be provided withmeasurements and analysis of financial value of the enterprise basedupon future events. As another example, the stakeholder may be one ofthe business enterprise's customers. In which case, customers may beperiodically surveyed to identify their expectations with regard tovalue creation and their level of satisfaction. The results of thesurvey may be stored in the database 104 and tracked over time so thattrends in the survey results may be analyzed. It will be apparent thatdata relevant to other types of stakeholders, such as employees,suppliers and business partners, or the community or society at large,may be included in the database 104. The database 104 may store suchparameters in a matrix referred to herein as the stakeholders' matrix.

While data in the database 104 can be accessed from any of theseperspectives as appropriate, for convenience, a specific dataset (e.g.,a collection of assumed variables and events) is primarily associatedwith each particular perspective. Thus, a unique data structure ormatrix may be associated with each of the four different perspectives.

The value realization context permits selection of one of a number ofvalue realization outcome displays, including outcome displays thatprovide information similar to that provided by conventionaltransaction-based accounting systems. However, in accordance with theinvention, the outcome displays are provided by applying an appropriatefilter and calculation engine to the event-based information in thedatabase to generate the selected report.

FIG. 1B is a diagrammatic view of initial choices (initial selection105) available to a user in determining whether to view value creation(value creation mode 106) or value realization information (valuerealization mode 107).

FIG. 2 illustrates a block diagrammatic view of a software architecture200 for enabling the value creation mode of the present invention forthe computer system 100 of FIG. 1A. The software architecture 200includes a number of software modules 202-220, each of which controlsthe CPU 102 to perform certain functions, as explained herein. Anintegration module 202 reconciles the four different perspectives andtransfers information among them. Thus, for example, if data stored inthe matrix associated with the value creation formula perspective ischanged, the integration module 202 ensures that corresponding datastored in the matrices associated with the other perspectives isappropriately updated. As shown in FIG. 2, the integration module 202interfaces with a formula matrix module 204, an event matrix module 206,a capacity matrix module 208 and a stakeholders' matrix module 210.

The formula matrix module 204 manages the data matrix stored in thedatabase 104 (FIG. 1A) which is relevant to the formulation of astrategy for the business in creating and realizing value. The eventmatrix module 206 manages the data matrix stored in the database 104which is relevant to the value stream model perspective. The capacitymatrix module 208 manages the data matrix stored in the database 104which is relevant to the value creation capacity perspective. Thestakeholders' matrix module 210 manages data stored in the matrix thatis relevant to the multiple stakeholders' perspective.

The formula matrix module 204 interfaces with a major premises module212. The major premises module 212 allows a user to input and alterassumed variables stored in the database 104 (FIG. 1A). These may be,for example, assumptions regarding the industry of which the businessenterprise is a part. The major premises module 212 also interfaces witha success criteria module 214 that allows a user to input and altermeasures of success for the business enterprise.

The major premises module 214 also interfaces with a strategic decisionsmodule 216. The strategic decisions module 216 allows a user to definedifferent decision trees, within the data matrix associated with theformula matrix module 204, which depend upon various strategic optionsavailable to management of the business enterprise. The strategicdecisions module 218 also interfaces with an other formula elementsmodule 218 that allows a user to input and alter other criteria relevantto evaluation of the value creation performance of the businessenterprise.

The other formula elements module 218 also interfaces with a scenariogrouping module 220. The scenario grouping module 220 allows a user toassemble existing data and to add additional data representative ofalternate scenarios for the future of the business enterprise. Forexample, a base case scenario 222 may be established by a particularassemblage of events and related assumptions (e.g., assumed variables)for the business enterprise. For example, the base case scenario mayinclude a current operational scenario that the business enterprise isimplementing. One or more additional alternate scenarios 224 may also beestablished including a different set of events and related assumptionsfor each alternate scenario. For example, the alternate scenarios may beunder consideration for possible future adoption by the enterprise.

Thus, in value creation mode, the system 100 (FIG. 1A) provides anability to analyze scenarios, consisting of particular groupings ofevents and related assumptions. As a result, a user may be provided witha plurality of outcomes 226 for the base case scenario, taken from eachof the four perspectives. In addition, the user may be provided with aplurality of alternate outcomes 228 for each alternate scenario.

As is described herein, the same underlying determinations made by thesystem 100 in value creation mode can be deployed in two principal“contexts” (e.g., conditions under which determinations are employed).In a first context, the system 100 generates comparisons between thebase case and alternative future scenarios. Thus, the first context(also referred to herein as “vision view”) facilitates the choice of anoptimal future scenario to maximize value creation of the businessenterprise. Accordingly, the first context is particularly useful forstrategic planning. In a second context, the system 100 compares theorganization's actual value creation performance during a period of timeto the performance predicted at the beginning of that time period. Thus,in the second context (also referred to herein as “performance view”),the value creation performance of the business enterprise may beevaluated with the benefit of hindsight and measured against valuecreation that was previously predicted for the enterprise.

FIG. 3 illustrates a flow diagram 300 showing determination of outcomesin value creation mode based upon different assumptions. For example,the CPU 102 can be controlled to determine the outcomes 226 (FIG. 2)from the groups of scenarios 220 (FIG. 2) in accordance with the flowdiagram 300 of FIG. 3. In a state 302, data relevant to the variousscenarios may be retrieved from the database 104 (FIG. 1A) to the CPU102 (FIG. 2). Then, in a state 304, the data for the assumptions andtheir related events may be assembled into scenarios.

As explained above, the event matrix stored in the database 104 is arelational database in which assumptions (e.g., assumed variables),events, and their related probabilities are collected and grouped intothe various base case and alternative scenarios. Some assumptions may bescenario-independent and, thus, are constant throughout all thescenarios. Other assumptions, however, may vary scenario by scenario.Thus, for example, an assumption (“Assumption a”) may be set at value a₁in the base case scenario, at value a₂ in a first alternate scenario(“Scenario A”), and at value a₃ in yet another alternate scenario(“Scenario B”). Each of the scenarios yields “scenario stakeholderoutcomes” as further described below. The scenario stakeholder outcomes(and how they vary over time) for the base case may be used forperformance tracking. The other scenario outcomes may be used as“what-if” comparisons for strategic planning.

Next, program flow may move to a state 306 where equations fordetermining present value are applied to the events and assumptions forthe base case scenario (exemplary computations are discussed herein).Then, from the state 306, program flow moves to a state 308 whereoutcomes determined by the computations performed in the state 306 arepresented. For example, the outcomes may include a monetary amount (afinancial outcome) determined to be the present value of the futurevalue streams of the business enterprise based upon the base caseassumptions. Alternately, the outcomes may include measurements ofnon-financial value creation.

In addition, from the state 304, program flow may move to a state 310.In the state 310, equations for determining present value are applied tothe events and assumptions for the first alternate scenario (“ScenarioA”). Then, from the state 310, program flow may move to a state 312where outcomes determined by the computations performed in the state 306are presented. For example, the outcomes may include a monetary amountdetermined to be the present value of the future value streams of thebusiness enterprise, or a non-financial metric, based upon the ScenarioA events and assumptions. Further, from the state 304 program flow maymove to a state 314. In the state 314, equations for determining presentvalue are applied to the events and assumptions for the second alternatescenario (“Scenario B”). Then, from the state 310, program flow may moveto a state 312 where outcomes determined by the computations performedin the state 306 are presented. For example, the outcomes may include amonetary amount determined to be the present value of the future valuestreams of the business enterprise, or a non-financial metric, basedupon the Scenario B assumptions.

FIG. 4 illustrates a flow diagram 306 for determining net present valuebased upon value creation in accordance with the present invention. Forexample, the flow diagram of FIG. 4 may be performed in the state 306 ofFIG. 3. In a state 352, an amount of a projected cash inflow (“CashIN”)for a future financial value stream of the business enterprise may beadjusted by a factor that accounts for the time period between thepresent and the time that the cash inflow is expected. For example, thefactor may be an after-tax, risk-adjusted discount rate (“ra_atr”). Theamount of cash inflow, CashIN, may be an assumed variable thatinfluences a future financial value stream for business enterprise. Anevent may occur, for example, which triggers the cash flow. Next,program flow may move to a state 354 where the projected cash inflowdetermined in the state 352 may be adjusted by a estimated probabilitythat the cash flow will be realized. From the state 354, program flowmoves to a state 356.

In the state 356, any additional influences on the future financialvalue stream for the business (e.g., projected cash inflows) for thesame or additional future financial value streams may be adjusted, as inthe states 352 and 354 and summed (e.g., aggregated) to determine atotal present value for the future financial value streams of thebusiness enterprise. The computations performed in the states 352-356may expressed as follows (for example, the selected stakeholder categorymay be “shareholders”):

The present value of projected after-tax cash inflows may be given by:

${InPV} = {\sum\limits_{1}^{n}{{CashIN}_{i} \times \left( \frac{1}{1 + {ra\_ atr}} \right)^{i} \times {InProb}}}$where CashIN represents the projected after-tax cash inflow for aspecific year; ra_atr is the after-tax risk-adjusted discount rate(adjusted for industry and company-wide risks); InProb is theprobability (as assessed by the user or by management of the businessenterprise) of the inflows occurring; and InPV is the discounted presentvalue of cash inflows.

The value:

$\sum\limits_{1}^{n}{{CashIN}_{i} \times \left( \frac{1}{1 + {ra\_ atr}} \right)^{i}}$represents the conventional discounted cash flow (DCF) formula forcomputing a present value (PV) of CashIN₁ in year 1, CashIN₂ in year 2,etc.

In a state 358, an amount of a projected cash outflow (“CashOUT”) for afuture financial value stream may be adjusted by a factor that accountsfor the time period between the present and the time that the cashoutflow is expected. For example, the factor may be a risk-free,after-tax discount rate (“rf_atr”). Next, program flow may move to astate 360 where the projected cash outflow determined in the state 358may be adjusted by a estimated probability that the cash outflow willoccur. From the state 360, program flow moves to a state 362.

In the state 362, any additional projected cash outflows for the same orany additional future financial value streams may be adjusted, as in thestates 358 and 360 and summed to determine a total present value for thebusiness enterprise that is attributable to cash outflows. Thecomputations performed in the states 358-362 may expressed as follows(for example, selected the stakeholder category may be “shareholders”):

The present value of projected after-tax cash outflows is given by:

${OutPV} = {\sum\limits_{1}^{n}{{CashOUT}_{i} \times \left( \frac{1}{1 + {rf\_ atr}} \right)^{i} \times {OutProb}}}$where CashOUT represents the projected after-tax cash outflow for aspecific year; rf_atr is the risk-free after-tax discount rate; OutProbis the probability (as assessed by the user or by management of thebusiness enterprise) of the outflows occurring; and OutPV is thediscounted present value of cash outflows.

Next program flow moves to a state 364 where the total present value ofprojected cash outflows may be subtracted from the total present valueof projected cash inflows to determine a net present value for thefuture value streams of the business enterprise.

The net present value (NetPV) computed in the state 364 may be given by:NetPV=InPV−OutPV

where NetPV is the net of the present values of cash inflows andoutflows.

Then, program flow moves from the state 364 to a state 366 where theeffect of real options value (if any) included in any of theenterprise's strategies may be incorporated in the computation. Thus,the present value computed in the state 366 may be given by:TotNetPV=NetPV+RealOptValwhere RealOptVal is the “real options value” of the ability to defercertain expenses until future events suggest that further investment iswarranted (similar to taking an option on a stock before advancing thefull investment price of the stock). The real options value may bedetermined conventionally by reference to the Black-Scholes equation.

It will be apparent that the above formulas are exemplary and are takenfrom the perspective of a shareholder. Other formulas may be used tocalculate present values for any of the other stakeholder groups. Forexample, from the perspective of a stakeholder that is a joint venturepartner, the events, their associated probabilities of occurrence andtheir associated financial benefits will result in different financialoutcomes than those experienced by a shareholder.

FIG. 5 illustrates the flow diagram 306 of FIG. 4 including exemplaryprojected cash flows and related probabilities. The example considers acase where a pharmaceutical company anticipates the sale of rights tomanufacture a particular drug 3 years in the future for $10.000 million.Therefore, in the state 352, CashIN is equal to $10.000 million. Inaddition, the after-tax risk-adjusted discount rate, which is adjustedfor industry-wide and company-wide risks, is assumed to be 8%.Therefore, ra_atr used for this example for cash inflows is equal to0.08. Since with the drug project is just through Phase III ClinicalTrials, the probability that the drug will be approved by the Food andDrug Administration (FDA) and final commercialization is estimated at50%. Therefore, InProb for this example is 50%.

In that case, the above formula:

${InPV} = {\sum\limits_{1}^{n}{{CashIN}_{i} \times \left( \frac{1}{1 + {ra\_ atr}} \right)^{i} \times {InProb}}}$simplifies to:

${InPV} = {{10.000 \times \left( \frac{1}{1.08} \right)^{3} \times 50\%} = 3.969}$

Also in the example, the expenses associated with commercialization ofthe drug are estimated to be $2.000 million. The after-tax risk-freediscount rate, rf_atr, used for cash outflows is assumed to be 4%. Inaddition, the same probability of 50% is associated with the outflow.

Accordingly, the formula:

${OutPV} = {\sum\limits_{1}^{n}{{CashOUT}_{i} \times \left( \frac{1}{1 + {rf\_ atr}} \right)^{i} \times {OutProb}}}$simplifies to:

${OutPV} = {{2.000 \times \left( \frac{1}{1.04} \right)^{3} \times 50\%} = 0.444}$and soNetPV=InPV−OutPV=3.969−0.444=3.525

Depending upon the circumstances, the rates for ra_atr and rf_atr may belarger or smaller. In addition, under certain circumstances it may beappropriate to use a surplus cash after-tax short-term investment-rate(rather than an after-tax risk-free rate) for cash outflows.

Adding a real options value of $0.300 million (calculation not shown inthis example but may be performed in accordance with conventionaltechniques) yields:TotNetPV=NetPV+RealOptVal=3,525+0.300=3,825

As a more complex example, FIG. 6 illustrates the flow diagram of FIG. 3including exemplary values for various assumptions (e.g., assumedvariables). In the example, a fictional pharmaceutical company, referredto herein as “Company A,” is involving a larger company as a partner,referred to herein as “Big Pharma,” in all its clinical trials. As abase case scenario, license fees are assumed to be 60% for Phase Itrials, 60% for Phase II trials, and 100% for Phase III Trials andongoing royalties on subsequent commercialized sales are assumed to be20%. With this amount of projected license fees, no further capital isexpected to be required since the initial capital was raised with thebase case scenario in mind. Commercialization and related revenues isexpected to start in the year 2010. To determine the present value ofthe future financial value streams of the business enterprise takinginto account this base case scenario, computations may be performed inaccordance with the flow diagram illustrated in FIG. 4. However, thedetails of the computations are not shown in FIG. 6. The outcome for thebase case scenario, for example, may be a present value (PV) of $296million.

In addition, two alternative scenarios may be presented. In a firstalternate scenario (“Scenario A”), the company conducts the Phase Itrials on its own and only involves Big Pharma partner in Phase II andIII trials. Because of the lesser financial commitment of Big Pharma, itwould normally pay a higher royalty rate on ultimate sales. However,this scenario may require Company A to raise additional capital of $90million to make up for the missing Phase I license fees. As anoffsetting factor, commercialization and related revenues are expectedto start in the year 2009. This is because a Big Pharma has its ownongoing manufacturing operations to consider with research anddevelopment tending to be a minor sideline. Consequently, Company Aitself is expected to act more quickly than Big Pharma. Therefore,commercialization in Scenario A is expected to occur more quickly incomparison to the base case scenario.

Therefore, if Company A conducts the Phase I trials on its own, theywill be completed somewhat sooner, thus advancing the finalcommercialization date. In computing the outcome, the discounted cashflow calculations utilized to determine the present value reflect thelower license fees (unfavorable), the higher royalty rates (favorable),and the earlier commercialization date (favorable). The net effect inthis assumed example, is a computed present value (PV) of $204 million.Clearly, at present, Company A achieves a better outcome with the basecase scenario. Accordingly, the better choice is to direct the companyalong the path indicated by the base case scenario.

Various factors, however, may change over time. If, as a result ofrevised assumptions (revenues, costs, timing, etc.) the recomputedScenario A ever turns out to be more favorable than the recomputed basecase scenario, then Company A will likely change its strategic decisionsand opt for Scenario A.

In a second alternate scenario (“Scenario B”), Company A conducts thevery long and expensive Phase III trials on its own and involves BigPharma as a partner in only the Phase I and II trials. Compensatingfactors expected to result from this more significant change are anincrease of the royalty rate to 28% and acceleration of the commencementof commercialization to the year 2008. However, Company A may have toraise an additional $300 million capital to finance the Phase IIItrials. When the present value is computed with all of these changesfactored in, present value under Scenario B may be found to be $231million. Again, the base case scenario at remains the most favorable.Updated assumptions may continue to be collected in the database 104(FIG. 1A) for each of these scenarios, as various events transpire sothat, at any time, management can decide to change strategic directionshould an alternative scenario prove optimal at some point in thefuture.

FIG. 6 also shows the comparative values for the Big Pharma stakeholder.While this is not shown in the example, the system may generate thepresent value of the base case and each alternative scenario formultiple stakeholders. The difference in the computations is that fromthe perspective of the Big Pharma company there will be differentassumptions made about cash inflows and outflows and their associatedprobabilities.

Some scenarios may eventually cease to be viable alternatives. Forexample, assuming Company A has contracted with Big Pharma toparticipate in the Phase I Clinical Trials, Scenario A is no longer acontinuing option. As such, Scenario A may be dropped from the database104 (FIG. 1A). Depending on how the contract with the Big Pharma hasbeen drawn up, however, Scenario B may continue to be a viable optionthat may be revisited at a later time (e.g., as the time for the PhaseIII Clinical Trials draws closer).

As noted above, a “financial value stream” refers to those benefits thatare reducible to cash or cash equivalents, whereas, a “non-financialvalue stream” refers to those benefits which are not readily reducibleto cash and cash equivalents. More specifically, non-financial valuestreams are quantified by various metrics that measure value creationperformance of the business enterprise with respect to the valuecreation expectations of stakeholders. Those value creation expectationsare related to benefits that are not readily reducible to cash and cashequivalents. A non-financial outcome is an expected quantification, suchas a numeric value or a yes/no result, expected to result from aparticular non-financial value stream.

As is the case future financial value streams, the determination ofnon-financial value streams or outcome metrics can be viewed in eithervision view, in which case the system calculates a future projectedoutcome based on assumed variables, or in performance tracking view,where the system compares a target or future outcome with actualachieved performance.

To further illustrate, numerous non-financial value streams related toexpectations of various categories of stakeholders are possible. Anexample of a non-financial value stream for stakeholders who arecustomers is “on-time performance.” For Company A, a pharmaceuticalcompany, a quantifiable metric for on-time performance may be the numberof drug formulas which are delivered on, or ahead of, a predefinedschedule in a given year. This metric may be predicted by computing anoutcome based upon assumed variables and influencing events. Inaddition, historic values for this metric may be measured and comparedto the predicted values. FIG. 7 illustrates a chart 350 showing acomparison between targeted and actual numbers of drug formulasdelivered on or ahead of schedule.

The on-time Performance relates to the expectations of a class ofstakeholders of Company A (e.g., customers). An exemplary formula forcalculating a metric for on-time performance (i.e. a non-financialoutcome) in vision mode (i.e. the metric is prospective of on-timeperformance rather than historic) may be as follows:future (or target) on-time performance=(A×D)+(A×E)+(A×F)Where assumed variables are as follows: A is the number of active drugdevelopment projects; D is the percentage of projects expected togenerate viable formulas in the current year; E is a factor that isrelated to innovation capabilities defined in a capacity matrix; and Fis a factor that is related to employee productivity which is related toemployee value creation in the stakeholder matrix.

Each of these assumed variables may be linked to an event in theevent/assumption matrix stored in the database 104 (FIG. 1A). Forexample, the assumed value, A, for the number of active drug developmentprojects may change if an event occurs defined as the company launchingone or more new projects. As another example, the percentage, D, ofprojects expected to generate viable formulas in the current year may belinked to past external events (e.g., an industry average). Further, thefactor, E, in the capacity matrix may also be linked to future eventsrelating to innovation. Also, the factor, F, in the stakeholder matrixmay be linked to future events relating to employee productivity whichis linked to company performance with respect to respect and recognitionof employees.

As shown in FIG. 7, the calculated target outcome for 2001 is 10. Thisvalue may result from the following assumed values:

A=25 (there are 25 active drug development projects);

D=60% (based on industry averages, 60% of these projects should resultin generating a formula for further testing and development);

E=−20% (since Company A was recently established, its innovationcapability is still ramping up, and E is assigned a value thatrepresents a discount attributable to lower innovation capability thanthe industry average); and

F=0% (is it is assumed that the company will meet the value creationexpectations of employees with respect to respect and recognition, withthe result that this event/assumed variable has neither a positive ornegative influence on the outcome).

In a performance tracking mode, the previously calculated outcome valuefor on-time performance (in vision mode) may be compared to actualhistoric performance. Significant differences between anticipated andactual performance may be indicative of a performance problem in thecompany that management should address, or alternatively, may indicatethat assumed variables are incorrect and the model needs to bere-calibrated accordingly. Thus, FIG. 7 shows exemplary historic valuesfor each of the years 2000, 2001 and 2002 compared to projected outcomevalues for those same years.

The metric for on-time performance may, in turn, be linked to otherfinancial or non-financial assumed variables and related events. Forexample, the event/assumption matrix may contain an event related tocustomer expectations with respect to on-time performance. A significantdiscrepancy between previously projected on-time performance (in visionmode) and actual on-time performance (in performance-tracking mode) maytrigger this event, which in turn may be linked to assumed variableswhich influence the timing of future commercialization revenues. Thus, acomputed non-financial outcome may be an event which triggers acomputation of a financial outcome and may also be an input (e.g., byinfluencing an assumed variable) to the computation of the financialoutcome.

Another example of a non-financial value stream for stakeholders who areemployees is “respect and recognition.” An example of a metric forrespect and recognition may be the number of employees who are awardedofficial recognition by company management in a given year. Anotherexample of a metric for respect and recognition may be attrition rate ofemployees in a given year. A further example of a metric for respect andrecognition may be results of a survey of, or feedback from, employeeswhich asks them to assess how well company management is doing in thisregard.

An example of a non-financial value stream for stakeholders who areshareholders is “access to information.” An example of a metric foraccess to information may be a number of press releases generated by thecompany in a given year. Another example of such a metric may be resultsof a survey of, or feedback from, shareholders which asks them to assesshow well company management is doing in this regard.

An example of a non-financial value stream for stakeholders who aresuppliers is “collaboration on new opportunities.” An example of ametric for this value stream may be a number of new supply channelsopened to a given a supplier in a given year. Another example of such ametric may be results of a survey of, or feedback from, suppliers whichasks them to assess how well company management is doing in this regard.

An example of a non-financial value stream for stakeholders who are thecommunity and society at large in which the company operates may be“environmental responsibility.” An example of a metric for this valuestream may be measured levels or quantities of various recognizedenvironmentally hazardous substances that are generated by the company.Another example of such a metric may be results of a survey of, orfeedback from, members of the community which asks them to assess howwell company management is doing in this regard.

The various non-financial value streams and non-financial outcomes maybe grouped into the following categories: capability metrics;infrastructure metrics; and networks metrics. Accordingly, events andassumed variables which influence these non-financial value streams andoutcomes can be stored in corresponding matrixes in the database 104,along with the events and assumed variables which influence financialvalue streams.

An example of a non-financial outcome in the above-described capabilitymetrics category is “annual intellectual property (IP) filings.” FIG. 8illustrates a chart 352 showing a comparison between targeted and actualnumbers of IP filings made (e.g., a number of patent applications). Todetermine the number of annual IP filings as a non-financial outcomemetric in vision mode (i.e. prospectively) for Company A, a formula maybe expressed by:future (or target) annual IP filings=A×B×CWhere assumed values are as follows: A is the number of active drugdevelopment projects;

B is the average number of scientists per development project; and C isthe average number of patents targeted per scientist per year.

Each of the assumed values may be linked to an event in theevent/assumption matrix stored in the database 104 (FIG. 1A). Forexample, the assumed value, A, for the number of active drug developmentprojects may change if an event occurs defined as the company launchingone or more new projects. As another example, the assumed value, B, forthe number of scientists per development project may change if thecompany an event occurs defined as a success in recruiting a targetedgroup of scientists. Accordingly, occurrence or non-occurrence of eventsin the event matrix may trigger computation of a non-financial outcome.

As shown in FIG. 8, the calculated value for 2001 is 375. This mayresult from the following assumed values:

A=25;

B=6; and

C=2.5.

In a performance tracking mode, the calculated outcome value for annualIP filings may be compared to actual performance. Thus, as shown in FIG.8, projected values are compared to actual values for the years 2000,2001 and 2002. Significant differences between anticipated and actualperformance may be indicative of a performance problem in the companythat management should address, or alternatively, may indicate thatassumed variables are incorrect and the model needs to be re-calibratedaccordingly.

As noted above, the value for annual IP filings in performance-trackingmode may, in turn, be linked to other financial or non-financial assumedvariables and related events. The system 100 (FIG. 1A) may compare theactual performance in annual IP filings with a previous calculation ofannual IP filings in vision mode. A significant discrepancy may triggeran event in the event/assumption matrix related to annual IP filingswhich, in turn, may trigger computation of a financial value. Forexample, the annual IP filings event may influence assumed variablesrelated to future licensing revenue from patents.

An example of a non-financial outcome in the above-describedinfrastructure metrics category is “supercomputing capacity.” FIG. 9illustrates a chart 354 showing a comparison between targeted and actuallevels of normalized computing capacity, for example, measured inmillions of instructions per second (MIPS). An example of anon-financial outcome in the above-described network metrics category is“global human genomics extranets.” FIG. 10 illustrates a chart 356showing a comparison between targeted and actual participation inextranets by targeted institutions.

As can be seen, these non-financial value streams and outcomes are notreadily reducible to financial values, however, they may influencefinancial value streams. Thus, the non-financial value stream metricsand non-financial outcome metrics generated by the system can be groupedinto two categories: those which produce outcome metrics that arethemselves classified as events for purposes of generating financialvalue creation outcomes and hence, may result in modifications tofinancial value creation outcomes; and those which are not classified asevents.

An example of a non-financial outcome which may, itself, be a eventwhich influences a financial value stream is the annual IP filingsmetric, as discussed above. An event in the event/assumption matrix maybe related to whether annual IP filings are significantly above or belowa predefined threshold. An assumed variable related to this event may befuture licensing revenue, which in turn will influence future financialvalue streams. Thus, if the non-financial outcome indicates that annualIP filings are above the predefined threshold, this fact may result inan increased probability that revenue will be derived from technologylicensing activities. Accordingly, a probability applied to determine apresent value of a future financial value stream, as explained herein,may be increased, which will, in turn, increase the present value forthe corresponding value stream.

Another example of a non-financial outcome which may influence afinancial outcome is the metric representative of employee respect andrecognition, as discussed above. The performance of the company inmeeting this expectation may be tracked, for example, by a survey ofemployees. An event in the event/assumption matrix may be related towhether such a survey reveals that company performance in this respectis significantly below or significantly above a defined threshold. Anassumed variable related to this event may be employee productivity,which in turn may influence the amount and timing of future financialvalue streams. In addition, this metric of respect and recognition mayalso influence other non-financial value streams, such as that relatedto on-time performance.

Thus, events may be linked to non-financial metrics (and vice versa),including future non-financial value streams (e.g., stakeholderexpectations with respect to value creation to the extent these arenon-financial) and to non-financial outcomes in the capacity matrix(e.g., capabilities, infrastructure, networks). In addition, certainnon-financial metrics, in turn, are defined as events in theevent/assumption matrix and, hence, may influence future financial valuestreams in addition to future non-financial value streams.

As mentioned, non-financial outcomes may be determined based uponassociated assumed variables and their influencing events. A formulamatrix may be created for an enterprise and stored in the database 104(FIG. 1A). The formula matrix may define, for example, what financialand non-financial value streams are to be modeled, what key scenariosmust be examined in the event/assumption matrix, what key capabilitiesmust be tracked in the capacity matrix, what the relevant stakeholdergroups are that must be incorporated into the stakeholder matrix, etc.In other words, the formula matrix sets up the key parameters of theoverall system.

Events and assumed variables are organized in several data structures.Events and assumed variables related to financial value creationoutcomes are organized in the event/assumption matrix, as describedabove. Assumed variables relating to non-financial value streams oroutcomes may be organized in a stakeholder matrix or a capacity matrixin the database 104. All assumed variables that have an influence on afuture financial or non-financial value stream of the businessenterprise are linked to at least one future or past event for eachassumed variable that influences the corresponding assumed variable.Note that some assumed variables may be located in the capacity orstakeholder matrix, but may be linked to events in the event matrix. Inaddition, certain outcome metrics relating to capacity or stakeholdersmay be events in the event/assumption matrix.

A generic formula for calculating a metric that represents anon-financial value stream or non-financial outcome may be given asfollows:Non-financial outcome metric=f(assumed variables_(1-n))where n=the number of assumed variables linked to events thatinfluencing the specified non-financial outcome. Thus, the non-financialoutcome metric is a function of a number, n, of assumed variables.Software which controls the CPU 102 to determine the financial andnon-financial outcomes as explained above is referred to herein as the“calculation engine” 400 (FIG. 22).

FIG. 11 illustrates an event matrix data structure 400 for storingassumptions (e.g., assumed variables) and their related events inaccordance with the present invention when operating in value creationmode. As stated previously, the event matrix 400 stored in the database104 (FIG. 1A) is a relational database in which assumptions, events, andtheir related probabilities are collected for both financial andnon-financial value streams. The system 100 is event-driven. That is,each assumption is based on various projected events that are expectedto influence the related assumption. If over a period of time, theprojected future events all come to pass exactly as anticipated, thenthe assumptions in the matrix 400 remain unchanged. However, if aprojected event does not occur, or if it occurs in a different way or toa different extent than originally projected, or if a previouslyunanticipated event occurs, then the related assumption may be modifiedin the matrix 400.

In FIG. 11, the matrix 400 contains the assumed variables that areutilized as a basis for computing the outcomes (e.g., present value forfinancial values streams or outcomes associated with non-financial valuestreams) of the future financial and non-financial value streams of thebusiness enterprise, the related projected events (e.g., a related eventstream) upon which the assumptions depend, and management's assessmentof the probability of those events occurring. Theassumption-event-probability relationships within the matrix 400 can bedisplayed in either of two ways. In an “assumption view,” the system 100presents the assumptions and, for each assumption, shows the influencingevents. The assumption view is shown in FIG. 11. In an “event view,” thesystem 100 focuses first on events and, then, for each event shows the“affected assumptions.” The event view of the event matrix 400 is shownin FIG. 13.

As an illustration, FIG. 11 (assumption view) shows that “Assumption a”is influenced by Event Streams 1, 2, and 3, while “Assumption b” isinfluenced by Event Streams 2, 4, and 5. Note that more than oneassumption may be influenced by the same event stream (e.g., bothAssumption a and Assumption b may be influenced by Event Stream 2).

Each event stream can be further decomposed into specific componentevents in that stream. Thus, Event Stream 1 may include projected Event1-1, Event 1-2 and Event 1-3. For each event, the matrix 400 may includeadditional information. This may include, for example,

an anticipated date of occurrence, a probability of occurrence (asassessed by management), what will constitute evidence of occurrence, ifand when the event occurs, and, prior to the event actually occurring,evidence of increasing likelihood that it will occur. In addition,evidence of decreasing likelihood that it will ever occur may beincluded. Also, an observer may be designated who will be charged withthe responsibility of assessing these early warnings (whether evidenceof increasing likelihood or evidence of decreasing likelihood) and forobserving actual evidence of occurrence if the event, in fact, occurs.These observer-reported observations regarding the event stream may becontinuously fed into the matrix 400, which in turn will affect theassumptions and therefore the projected outcomes based upon computationof the present value. Because the occurrence or non-occurrence of anevent may trigger a re-computation of one or more of the outcomes, thesystem 100 (FIG. 1A) may be said to be event-driven.

FIG. 12 illustrates the event matrix data structure 400 of FIG. 7including exemplary assumptions and related events. In this example of asmall portion of the event matrix 400, i.e., three assumptions and theirrelated events, are considered. One is the assumption that Company Awill earn a royalty rate of 20%. This assumption, in turn, will beinfluenced by three identified event streams: changes in competitorroyalty rates, which would influence Company A's negotiations withpotential Big Pharma partners; changes in the growth rate of world drugsales (e.g., a markedly higher rate might put downward pressure onroyalty percentages); and Company A's negotiating success with other newpotential partners (e.g., success in other negotiations would make theassumed royalty rate more likely).

Another assumption in the example is the assumed market growth rate forbio-tech drugs of 15% a year. This is a relatively high growth rate butreflects the explosion of opportunities that are anticipated to followthe impending completion of the Human Genome Project (the completemapping of the human genome). This assumed future growth rate will beinfluenced by three identified event streams: changes in the currentgrowth rate of world drug sales (e.g., a downturn in the current ratewould suggest the possibility of a lower than previously forecast futuregrowth rate); a change in the health care delivery system in China(e.g., certain developments would open up that country for westernbio-tech drugs, which would double or triple the potential market size);and the impact of non-drug therapies (e.g., if they increase inpopularity, there may be a downturn in drug sales).

A third assumption in this small portion of the matrix 400 is thelongevity assumption that a new Company A drug will last for 10 yearsafter commercialization before it becomes obsolete as a result of a new,leap-frogging scientific discovery.

Each of the event streams can be further analyzed into specificcomponent events in that stream. In this example, the event stream“changes in competitor royalty rates” contains at least three events.The rumored deal with a competitor (referred herein fictionally as“Company B”) would raise the bar and generally lead to higher royalties.Such a deal might occur by Jun. 1, 2000 but Company A managementattributes a probability to this happening of only 10% to 20%. If itever occurs, it will be immediately publicized by the scientific media.

In the meantime, whether talks are continuing (increasing likelihood) orbecome stalled (decreasing likelihood) is something that designatedobserver “Anne Smith” is charged with the responsibility of monitoring.It is expected that the next relevant observation she can likely makewill be around Mar. 1, 2000, although unexpected changes in timetableare possible. Another anticipated influencing event is the impact of newEU protocols that could have the effect of lowering royalty ratesgenerally. Company A management estimates that there is only a 5% to 10%probability of these protocols ultimately being agreed upon. If they areadopted, it would most likely be on Jul. 15, 2000 following the July EUConference. Evidence of increasing likelihood would be progress in theconsideration of the recent German proposals while decreasing likelihoodwould be suggested if the German proposals get dropped. Designatedobserver, “Kurt Heigel” will be monitoring this situation and willlikely have an updated observation to make by mid April.

Finally, the impact of a recent merger of another competitor (referredto herein as “Company C”) could have a minor reducing influence onroyalties and Company A management estimates the effect is 50% probable.The effect is anticipated to be more likely if it turns out that theFrench senior management team of Company C is replaced and less likelyif it turns out that there will be no reorganization of the Frenchsubsidiary. A designated observer, “Étienne Dupuy” may be monitoringthis situation and will likely have an updated observation to make byearly July.

The event matrix 400 also characterizes each assumption by type. Havingsuch an organized typology of assumptions helps to assure that allrelevant assumptions have been identified and stated explicitly.Assumptions can be classified, for example, as: revenue assumptions;expense assumptions; discount rate assumptions; and timing assumptions.

Another aspect of the system 100 (FIG. 1A) may be an organized typologyof events. For example, events may be characterized as follows: (a)enterprise events, which are internal to or involving the enterprise,and which include: relational events (e.g., negotiations with apotential strategic partner); operational events (e.g., the completionof Phase II clinical trials); contractual events (e.g., the signing of aroyalty agreement); transactional events (e.g., the receipt of licensefees); observational events (e.g., observations made during marketingresearch); and decisional events (e.g., the decision to drop Drug A anddevelop Drug B); (b) external events, which are wholly outside theenterprise but ultimately influencing it, and which include: marketevents, which affect an entire industry; competitive events (e.g., thethreat of a newly successful competitor); and supply events, whichaffect the availability of needed resources; (c) event implications,which include: new opportunities, which are clearly indicated; newconfirmatory evidence that the future is unfolding as previouslyassumed; new contradictory evidence that the future may not be unfoldingas assumed; and new threats, which are clearly identified.

FIG. 13 illustrates an event matrix data structure for storing eventsand their related assumptions in accordance with the present inventionwhen operating in value creation mode. As mentioned, in the event view,the system 100 (FIG. 1A) displays events and, then, for each event showsthe affected assumptions. In this figure, the event streams shown areEvent Stream 1, Event Stream 2, and Event Stream 3. The first affectsAssumptions a, d, and e; the second affects Assumptions a, b, and f; thethird affects only Assumption a.

In addition, assumptions (i.e. assumed variables) stored in the eventmatrix 400 (FIGS. 11-13) are preferably arranged in a hierarchy(referred to herein as an “assumption hierarchy”). Thus, an assumptionat one level may be influenced by assumptions at one or more lower, moredetailed, levels. These lower level assumptions may be considered“underlying assumptions” relative to the assumptions which areinfluenced by them. For example, management of the business enterprisemay assess that the probability of a particular revenue-generating eventoccurring over a six-month period is 30% for the first month, 10% forthe second month, 7% for the third month and 1% for each of the fourth,fifth and sixth months. These assumptions for the individual months areunderlying assumptions relative to an overriding assumption that theevent has a 50% probability of occurring within the six-month period(30%+10%+7%+1%+1%+1%=50%). This overriding variable of 50% and theunderlying variables of 30%, 10%, 7%, 1%, 1% and 1% may be stored in theevent matrix 400 and may be inserted into a calculation of present valuefor that particular value stream. If the first month passes without theevent occurring, then the 50% value may be reduced to 20%(10%+7%+1%+1%+1%=20%) and the present value determined again based uponthe new, lower probability.

The system 100 (FIG. 1A) may determine four types of outcomes for eachstakeholder: financial value creation, which includes the Present Valueof future value creation streams;

non-financial value creation, which includes appropriate metrics toreflect value streams that cannot be conveniently denominated in cashand cash equivalents; financial value destruction, which includes thePresent Value of future value destruction streams; and non-financialvalue destruction, which includes appropriate metrics to reflect valuedestruction potential that cannot be conveniently denominated in cashand cash equivalents.

In any venture, there is always the potential for the loss of one'sinitial investment if the project fails. In such a case, the presentvalue would be zero. However, it is not always that case that one'spotential loss is limited to one's initial investment. Accordingly, thefinancial value destruction calculation is relevant in situations wherethe potential loss is greater than the investment at risk. FIG. 14illustrates a flow diagram 500 for determining the effect on presentvalue based on financial value destruction and its related probability.

The steps for calculating financial value destruction parallel thosedescribed herein for calculating financial value creation. In a state502, a projected after-tax cash value is ascertained for a financialvalue destruction instance. Then, program flow moves to a state 504where the cash value is adjusted by an ascertained probability that thevalue destruction will occur. For example, the cash value may bemultiplied by the probability. From the state 504 program flow moves toa state 506. In a state 506, a result of the adjustment performed in thestate 504 may be presented.

FIG. 15 illustrates the flow diagram of FIG. 14 including an exemplaryvalue destruction and related probability. In the value destructionexample, Company A has become aware that under one scenario underconsideration, if it decides to terminate a certain project, it riskslosing one of its key lead scientists, which may in turn result in aloss of key contacts that are essential to the success of a second majorproject valued at $2 million. Thus, the cash value ascertained in thestate 502 is $2 million. The probability attached to this combination ofcircumstances is 10%. Thus, in the state 504, when discounted at 8% (anafter-tax non-risk adjusted discount rate, “ua_atr”), and multiplied bythe 10% probability factor, the equation

${ValDestrucPV} = {\sum\limits_{1}^{n}{{ValDestruc}_{i} \times \left( \frac{1}{1 + {ua\_ atr}} \right)^{i} \times {DestrucProb}}}$yields a present value of $79,000. This value may be presented as anoutcome in the state 506.

FIG. 16 illustrates a flow diagram for determining an outcome variancefor different future scenarios in accordance with the present invention.In states 602, 604, and 606 outcomes, such as present values, for eachof the base case scenario, and one or more additional scenarios (e.g.,Scenarios A and B) may be determined, as explained herein. For trackingperformance over time, the outcomes for the base case scenario may bedetermined with respect to a first point in time, while the outcomes forthe alternate scenarios may be determined with respect to a later pointin time.

Then, the various outcomes of these scenarios may be compared in states608 and 610. This may be accomplished, for example, by determining anoutcome variance using the following equation:

where t₂>t₁:OutcomeVar_(A>bc)=TotNetPV_(A)−TotNetPV_(bc)×(1+ra _(—) atr)^((t) ²^(−t) ¹ ⁾This equation is equivalent to taking the present value (PV) at thebeginning of the period in question, and adding a cost of capital return(COCr), and comparing the result to the calculated present value (PV) atthe end of the period.

If the outcome variance is zero, then the organization has earnedexactly the returns expected during the period. Normally, however, therewill be a difference between the actual present value (PV) and theexpected present value (PV) after adding the cost of capital return.

A next step that may be performed by the system 100 (FIG. 1A) in thestates 612 and 614 is an analysis of the changes in events and relatedassumptions that, in combination, account for the Outcome Variance. Thisanalysis may be important to ensuring management accountability for theselection of events and assumptions in the event matrix 400 (FIGS. 7,13).

A similar type of analysis can be performed to compare one or morescenarios at a particular point in time.

where t₂=t₁:OutcomeComp_(B>A)=TotNetPV_(B)−TotNetPV_(A)In the case, the equation is used to compare the outcomes of thescenarios under comparison. A similar analysis of the reasons for thedifference in outcomes can be performed to identify the criticaldifferences in events and assumptions between the scenarios and may beimportant to strategic planning for the enterprise.

FIG. 17 illustrates an exemplary determination of outcome variance. InFIG. 17, using the example for Company A, the calculation of an outcomevariance of $53.929 million is shown based on applying a cost of capitalreturn (COCr) to the present value (PV) at the beginning of the period(i.e. an opening present value), and comparing the result to thecalculated PV for the current period.

This is followed by an analysis of the changes in events and assumptionsthat account for the calculated difference. In this illustration, thedifference is accounted for by changes in 8 events or relatedassumptions:

Five changes in events or related assumptions caused PV to be higherthan previously calculated: (1) expected increase in future sales forBioInformatics Tool #4; (2) expected increase in biotech sales worldwide (which will also results in an increase in Company A sales); (3) arevision upward of the expected sales for Biotech Drug #26; (4) anupward increase in general sales growth based on the world salesincreases the previous; and (5) slightly higher investment incomeperformance.

Three changes in events or related assumptions caused PV to be lowerthan previously calculated: (1) slight overrun in R&D spending; (2) anexpectation that this overrun would continue into the future; and (3) ahigher donation to the World Health Organization (because of thepositive outcome variance).

FIG. 18 illustrates a flow diagram 700 for operation of the computersystem 102 of FIG. 1A including various modes of user interaction inaccordance with the present invention. Program flow begins in a startand user authorization state 702.

In the state 702, a verification of the identity of a user (e.g., astakeholder-user) who is attempting to access the system 100 (FIG. 1A)may be determined. This may include, for example, obtaining the user'sidentity, verifying the user's password and checking and recording atime stamp for the user' session. In addition, the user may berestricted from performing certain actions based upon the user'sidentity. Thus, different users may have different levels ofauthorization. This may include restricting the user to only be able toview certain designated information in the various matrices, or allowingthe user to also modify certain designated information. Further, theuser may be restricted to a particular mode (e.g., build mode oranalysis mode) and access method (e.g., intranet or extranet). Inaddition, the user may be restricted to a particular level of detailsuch that only certain designated levels of the assumption hierarchy maybe unavailable to the user for viewing or making changes. Generally,however, a user may be permitted to store an alternate assumption forany of the assumptions that the user is authorized to view. Assumingthat in the state 702, the stakeholder-user is authorized to proceed,program flow moves to a state 704.

The system 100 may support five different types of users when operatingin value creation mode. These may include: builders, who may bebuilding, installing or modifying the system 100; updaters, who may beupdating information (e.g., assumed variables) stored in the database104 (FIG. 1A); stakeholders, who may be using the system 100 to conductanalysis; assurers, who may have an responsibility to attest to theaccuracy of information provided by the system 100; and reporters, whomay wish to generate a report from the system 100. Accordingly, eachuser may be grouped or classified as a member of one of these groups oras a member of some other group, such as experts at value creationmodeling, according to the user's identification.

To accommodate these users, the system 100 may operate in five differentcorresponding sub-modes of operation. The modes include: a buildsub-mode, in which a builder may build, install or modify the system100; an update sub-mode, in which a updater may update information inthe database 104; an analysis sub-mode, in which a stakeholder mayconduct analysis; an assurance sub-mode, in which an assurer mayinteract with the system in order to perform various assuranceoperations, and a reporting sub-mode, in which a reporter may generatevarious outcome displays. Accordingly, in the state 704, the userselects a sub-mode of operation for the system 100 (FIG. 1A) under whichthe user may interact with the system 100, including interaction withdata stored in the database 104 (FIG. 1A).

The build sub-mode provides an interface by which the user mayinitialize the system 100 (FIG. 1A) for a particular businessenterprise. Accordingly, the build sub-mode is generally a startingpoint for a user who is starting from scratch to build a data set for aparticular business. This may include creating the event matrix 400, orother type of matrix in the database 104 (FIG. 1A).

More particularly, assuming the user selects the build sub-mode in thestate 704, program flow moves to a state 706. In the state 706, the usermay select a downloadable template from a plurality of such templates.For example, downloadable templates for various different industries,sectors, or functions performed by the enterprise may be pre-stored at acentralized location in the network 100 (FIG. 1A). For example, thetemplates may be downloadable from the Internet. Such a template mayassist the stakeholder-user in using the build sub-mode by providingsome of the information the database 104 (FIG. 1A) which the user wouldotherwise provide manually. This information could include assumptionsthat are typical for the industry or sector, and relevant to thefunctions performed by the enterprise, such as research and development,manufacturing, distribution, and so forth.

From the state 706, program flow moves to a state 708. In the state 708,the user may select one of the four perspectives on the businessenterprise (e.g., data arrangements) in which the user desires to workin the build mode. As mentioned, these perspectives include: (1)information relating to the enterprise's value creation and realizationformula; (2) information relating to the enterprise's value streammodel; (3) information relating to value creation capacity of thebusiness enterprise; and (4) information relating to value creation formultiple stakeholders of the business enterprise.

Assuming the user selects the value creation and realization formula,program flow may move to a state 710. In the state 710, the user mayspecify or modify the value creation and realization components for theenterprise. These may include, for example, success criteria, keydecisions, major premises, value creation capacity components, andidentification of key stakeholders.

Alternately, if in the state 708, the user selects the value streammodel, program flow may move to a state 712. In the state 712, the usermay specify or modify the value stream model for the enterprise. Thismay include, for example, identification of value streams and theirrelated events and assumptions and specifying how outcomes (e.g.,financial and non-financial) are to be determined based upon valuecreation and value destruction events.

If in the state 708, the user selects the value creation capacity,program flow may move to a state 714. In the state 714, the user mayspecify or modify the value creation capacity matrix for the businessenterprise. This may include, for example, identifying components (e.g.,capabilities, infrastructure and networks) needed by the enterprise torealize its value creation goals and identifying metrics for each ofthese components (e.g., capability metrics, infrastructure metrics andnetwork metrics).

If in the state 708, the user selects value creation for multiplestakeholders, program flow may move to a state 716. In the state 716,the user may specify or modify the multiple stakeholders matrix for thebusiness enterprise. This may include, for example, identifying relevantstakeholders (e.g., shareholders, customers, suppliers anddistributors), and identifying appropriate value creation metrics foreach (e.g., customer satisfaction levels or measures of how well theenterprise interacts with its suppliers and distributors).

From any of the states 710-716 program flow may move to an end state 718in which the session with the stakeholder-user may terminate.Alternately, program flow may return to the state 704 where thestakeholder-user may select another mode of operation for the system 100(FIG. 1A).

Assuming the user selects the update mode in the state 704, program flowmoves to a state 720. In the state 720, the stakeholder user may selectone of the four perspectives on the business enterprise in which theuser desires to work in the update mode. The update sub-mode provides aninterface by which a stakeholder-user to make updates to the data in thedatabase 104 (FIG. 1A) for a particular business enterprise. This mayinclude updating the event matrix 400 (FIGS. 11-13) as events occur thataffect assumptions and related value streams. Alternately, this mayinclude updating any of the other data, such as for the formula matrix,the capacity matrix or the multiple shareholders matrix, stored in thedatabase 104.

If the user selects the value creation and realization formula, programflow may move from the state 720 to a state 722. In the state 722, theuser may update information contained in the value creation andrealization formula. This may include updating the success criteria, keydecisions, major premises, capacity components and the stakeholdermatrix.

Alternately, if in the state 720, the user selects the value streammodel, then program flow moves to a state 724. In the state 724, theuser may update existing information and may record new information inthe event matrix 400 (FIGS. 11-13). This may include updating the eventsand assumptions as events occur and assumptions change over time. Forexample, a designated observer may make a change in response to theoccurrence or non-occurrence of an event. This may also include the userselecting a level of detail to view and record value stream information,such as at a designated level in the assumption hierarchy (assuming thatthe user has authorization to access information at the requestedlevel). In addition, the user may select a particular value stream outof several stored value streams

Preferably, each entry in the event/assumption matrix 400 (FIGS. 11-13)(and the related assumptions in the capacity matrix and the stakeholdermatrix) is tagged with a reference to the user who provided theinformation. For example, the user's identity may be stored in thedatabase 104 (FIG. 1A) in association with each element of informationwhich was provided by that user. Accordingly, the information may bearranged according to who provided the information. Thus, a complete setof entries may be tagged and grouped as provided by management of thebusiness enterprise. This grouping can be considered a base case or“official” scenario.

Each other stakeholder-user, or group of users, may develop alternatescenarios. For example, a user may substitute one or more of their ownassumptions for those of the base case scenario to develop an alternatescenario. Similarly, the alternate scenarios of individual users may begrouped. Accordingly, in the state 724, the user may also select aparticular scenario, out of the base case scenario and several storedalternate scenarios, in which the user may change any informationrelating to a particular event or assumption. For example, FIG. 19illustrates an exemplary arrangement of data in the event matrix 400including some entries from the base case scenario and other entriesfrom other users (in this case, Users A, B and C). The FIG. 19 showsthat user identities are stored in association with their storedassumptions. Three events are depicted in the event/assumption matrix400. Event 1 was defined by Management, as was Assumption a. Users B andC, however, have provided alternative values for Assumption a. Event 2was defined by Management. Assumptions b, c, and d are related to Event2, and no alternative values have been provided by users. Event 3,however, was added by User A, as was the related Assumption e. User B,who has been authorized to view the stored assumptions of User A, hasdefined an alternative value for Assumption e.

FIG. 20 illustrates groupings of information from the matrix 400 whichwas provided by various stakeholders. This includes the official basecase scenario and multiple alternate scenarios for stakeholder-users (inthis case, User A, User B and User C). The alternate scenarios may befurther arranged, as shown in FIG. 20, in groups according to thecontributors of the alternate assumptions (in this case, Users B and C).Each stakeholder-user when using the system 100 may have an opportunityto specify what perspective to work with (e.g., formula, value streammodel, capacity, or stakeholder perspectives) and to specify theparticular user or group of users (e.g., the management perspective orthe management perspective as modified by the selected user or usergroup) who provided the data that the user to work with. For example,User A can look at the alternations to the base case made by User B andC individually, and at the alterations to the base case of Users B and Cas a Group (e.g., Group 1, as represented in FIG. 20 by the dotted linerectangle).

More particularly, each user, if authorized to do so, may choose toamend an “official” base case scenario, amend an official alternativescenario, or create their own alternative scenario. In addition, User Ahas the ability to view the combined changes made by a group of users—inthis case, Users B and C. Further, User C may give permission for User Ato review User C's customized scenarios. This functionality may limitedto company insiders, or alternatively, made available to outsiders, andeven, if the company uses the system 100 (FIG. 1A) to report informationexternally, investment analysts. In the preferred embodiment, each useris able to make changes to his or her alternative scenarios, but mayonly view the alternative scenarios of another user without makingchanges.

To facilitate grouping of contributions, users are preferably assignedto various user groups when first accessing the system 100. These groupsmay be used when authorizing users and groups of users to view storedassumptions and to make changes to them.

If, in the state 720, the user selects the value creation capacity, thenprogram flow moves to a state 726. In the state 726, the user may updateinformation contained in the capacity matrix of the database 104 (FIG.1A). This may include, for example, updating the metrics forcapabilities, infrastructure and networks or updating a specificcapacity component. This may also include the user selecting a level ofdetail prior to updating information in the capacity matrix.

In the state 720, the user may also select updating the stakeholdermatrix. In which case, program flow may move to a state 728. In thestate 728, the user may update information contained in the stakeholdermatrix of the database 104 (FIG. 1A). This may include, for example,updating stakeholder metrics or receiving feedback from the stakeholderregarding the value creation performance of the business enterprise fromhis or her perspective. Updating performed in the state 728 may alsoinclude the stakeholder-user selecting a level of detail at which thestakeholder information is presented and selecting a particularstakeholder perspective from among the various different stakeholders,prior to the user updating the information.

The system 100 (FIG. 1A) may provide real-time data collection toencourage stakeholder-users to provide feedback on the performance ofthe organization from their perspective. Appropriate filters may beestablished to ensure that the data obtained is meaningful andrepresentative. On-time performance can be used to illustrate thepotential for direct performance feedback from stakeholders. Customerscould be given the opportunity to provide their own feedback, from theirperspective, on Company A's on-time performance. If their feedbackconfirmed the internal information maintained by the company, thisfeedback would serve the validate the calculations with respect tocustomer value creation. On the other hand, if the feedback from thecustomer stakeholders indicated significant differences from thecompany's internal information, this could be indicative of incorrectinternal information, or alternative, incorrect perceptions on the partof customers. In either case, this information would alert Company A'smanagement to the need for action to address the problem. FIG. 21illustrates various metrics for which feedback may be provided by usersor stakeholders in accordance with the present invention.

From any of the states 722-728, program flow may move to the end state718, terminating the session with the stakeholder-user. Alternately,program flow may return to the state 704.

Assuming the user selects the analysis sub-mode in the state 704,program flow moves to a state 730. In the state 730, the user may selectone of the four perspectives on the business enterprise in which theuser desires to work in the analysis mode. The analysis sub-modeprovides an interface by which a stakeholder-user may assess the valuecreation performance of the business enterprise by reviewing the variousmatrices in the database 104 (FIG. 1A), making changes (e.g., formingalternate scenarios) and, then, reviewing projected outcomes based uponthe changes. Then, program flow may move from the state 730 to a state732.

In the state 732, the stakeholder-user may select a level of detail inwhich the selected value creation information is presented. For example,the user may select a specific level in the assumptions hierarchy(assuming that the user has appropriate authorization). The user mayalso select to review information regarding the business enterprise as awhole or information regarding a specific value stream.

If the user selected the value creation and realization formula in thestate 730, then program flow moves to a state 734. In the state 734, theuser may then review information from the value creation and realizationformula matrix stored in the database 104 (FIG. 1A). This may include,for example, reviewing the success criteria, key decisions, majorpremises, capacity components, information regarding key stakeholders,formula variance analysis information, benchmarking information andoutcome displays in various formats.

Alternately, assuming that the user selected the value stream model inthe state 730, then program flow moves to a state 736. In the state 736,the user may then review information from the event matrix which isstored in the database 104 (FIG. 1A). This may include, for example,selecting a specific value stream, scenario or time period for analysis.This may also include reviewing event entries, assumptions, benchmarkinginformation, outcome displays in various formats and outcomes. Theoutcomes reviewed in the state 736 may include, for example, present andfuture, financial and non-financial, value creation determinations,value destruction determinations, and outcome variance determinations.

If, in the state 730, the user selects the capacity matrix for analysis,program flow moves to a state 738. In the state 738, the user may thenreview information from the capacity matrix stored in the database 104(FIG. 1A). This may include, for example, selecting a specific capacitycomponent (e.g., capabilities, infrastructure or networks). For eachcomponent, this may also include reviewing the associated metrics. Inaddition, in the state 738, the user may also review variance analysis,benchmarking and outcome displays in various formats for the capacitymatrix.

Alternately, assuming that in the state 730, the user selects thestakeholder matrix for analysis, the user may review information fromthe stakeholder matrix. Accordingly, program flow may then move to astate 740. Analysis in the state 740 may include, for example, the userselecting a level of detail at which information regarding a stakeholderperspective is to be reviewed and selecting a specific stakeholderperspective from the several different stakeholder perspectives.Analysis in the state 740 may also include the user reviewingstakeholder metrics for the selected stakeholder perspectives. Inaddition the user may also review variance analysis, benchmarking andoutcome displays in various formats for the stakeholder matrix.

FIG. 22 illustrates an event/assumption filter 800 and calculationengine 802 for determining various different outcomes based on thestored assumptions of various users. In calculating future financial andnon-financial value streams, the system may select from the relationaldatabase 104 (FIG. 1A) entries that are tagged as contributed by theselected user or user group, and use those entries to feed into thecalculation of financial and non-financial value streams and othernon-financial outcomes.

As shown in FIG. 22, an event/assumptions filter 800 may be used toselect from the event matrix 400 (FIGS. 11-13) of the relationaldatabase 102 the appropriate events and related assumptions. In the caseof Situation A, the events and assumptions selected by the filter 800are the ones defined by management of the business enterprise and, thus,represent the base case scenario. These events and assumptions may thenbe submitted to the calculation engine 802, which applies the variousformulas and methods described herein for determining financial andnon-financial outcomes. Thus, the outcomes are per the events andassumptions as defined by management.

In the case of Situation B, the event/assumptions filter 800 may selectmanagement-defined events and assumptions, except in the case where UserA has stored one or more alternative assumptions, in which case thosealternative assumptions will be used. Thus, the outcomes determined bythe engine 802 are per the events and assumptions defined by User A.

In the case of Situation C, the event/assumptions filter 800 may selectmanagement-defined events and assumptions, except in the case where anymember of Group 1 has stored an alternative event or assumption, inwhich case those stored alternative event or assumptions will be used.Accordingly, the outcomes determined by the engine 802 are as per eventsand assumptions as defined by Group 1.

In cases where more than one member of Group 1 has stored an alternativeto a particular event or assumption, the default action of theevent/assumptions filter 800 may be to select the stored alternativewhich represents the greatest difference from the management-definedevent or assumption. The event/assumptions filter 800 may also beconfigured to use a calculated average or mean of stored events orassumptions for the selected group, and may be configured to prompt auser to make a specific selection among alternative stored events andassumptions. Further, the filter 800 may iterate through a number ofcalculations and produce a report showing a range of outcomes betweenthe most pessimistic and most optimistic stored events and assumptionsfor the selected group.

Note that these selections and determinations may be done at differentlevels of detail, depending on the levels of detail is permitted to theuser, as in state 702 (FIG. 18), or which the user has selected, as instate 732 (FIG. 18).

Situation D of FIG. 22 represents determination of outcomes based ondirect feedback recorded from stakeholders on performance. As mentioned,where authorized (as in state 702 of FIG. 18), a stakeholder-user may bepermitted to provide direct, real-time feedback to the enterprise on itsperformance with respect to that stakeholder's value creationexpectations, as in state 728 of FIG. 18. For example, astakeholder-user who is a customer that is authorized to provide directperformance feedback may have defined an expectation with respect toon-time performance. The system may determine an outcome for a futurenon-financial value stream with respect to on-time performance. Anauthorized stakeholder-user, in viewing the outcomes of the calculationswith respect to on-time performance may also choose to substitute adifferent value, based on their own experience related to on-timeperformance, for the outcome that would otherwise be calculated by thesystem.

In this situation, the event/assumptions filter 800 may substitute thestakeholder-provided value, or where many stakeholders have providedfeedback, may provide a sum or average (as appropriate) of thestakeholder-provided values, for the appropriate non-financial valuestreams. The calculation engine 802 may then determine financial andnon-financial outcomes, as described herein based upon the stakeholderfeedback.

From any of the states 732-740, program flow may move to the end state718, terminating the session with the stakeholder-user. Alternately,program flow may return to the state 704 where the stakeholder-user mayselect another sub-mode of operation for the system 100 (FIG. 1A).

Together, the update and analysis modes provide user interactivity tomake changes and view the results. Accordingly, the system 100 (FIG. 1A)may track user-defined assumptions and provide users with an ability toalter events and assumptions and see the impact of these changes oncalculated outcomes for each group of stakeholders. Preferably, thestakeholder-users may record their altered assumptions so that theircustomized scenarios will be available for review on their next visit,or by other stakeholder users, and can be customized further.

In sum, several aspects of stakeholder-interactivity have been describedincluding: a stakeholder-user storing events and assumptions that may beviewed and later modified on a subsequent visit; a stakeholder-userviewing the stored events and assumptions of other users or groups ofusers, and the outcomes of these stored events and assumptions, whereauthorized to do so; and management viewing a summary of stored eventsand assumptions to obtain the viewpoints of various groups ofstakeholders regarding the management-defined events and assumptions.This may result in management reviewing and updating themanagement-defined events and assumptions as appropriate. In addition, astakeholder-user may provide direct performance feedback to theenterprise on value creation performance. Management or other users may,in turn, determine the impact on calculated outcomes of substitutingdirect stakeholder feedback for the values otherwise calculated by thesystem 100 (FIG. 1A).

Returning to FIG. 18, assuming the stakeholder user selects theassurance sub-mode in the state 704, program flow moves to a state 742.The assurance sub-mode provides an interface by which stakeholder-userswith assurance responsibilities may review results of variousself-auditing routines and gather additional evidence necessary tosupport their attestation with respect to the value creationinformation. For example, this may include making sure there are noinconsistencies in the event matrix (e.g., inconsistent assumptions). Inaddition, this may include validating information in the database 104(FIG. 1A) by performing benchmarking by which the value creationperformance of the business enterprise is compared against otherenterprises in the same industry, or with similar characteristics.

In the state 742, the stakeholder-user may select an assurance template.For example, the assurance template may be downloadable from acentralized database and may contain pre-programmed self-auditingroutines that may be performed by the system 100 (FIG. 1A), and may alsosupport the gathering of specific types of evidence to support anassurance opinion. From the state 742, program flow may move to a state744. In the state 744, the user may select one of the four perspectiveson the business enterprise upon which the user desires to obtainassurance-related information.

Then, if the user selects the formula matrix, program flow moves to astate 746 where selected assurance-related information may be obtainedfrom, and selected assurance-related procedures, including self-auditingroutines, may be applied to, the formula matrix in the database 104(FIG. 1A). Alternately, if the user selects the event matrix, programflow moves to a state 748 where selected assurance-related informationmay be obtained from, and selected assurance-related procedures,including self-auditing routines, may be applied to, the event matrix inthe database 104 (FIG. 1A). Assuming the user selects the capacitymatrix, program flow moves to a state 750 where selectedassurance-related information may be obtained from, and selectedassurance-related procedures, including self-auditing routines, may beapplied to, the capacity matrix. Alternately, if the user selects thestakeholder matrix, program flow moves to a state 752 where selectedassurance-related information may be obtained from, and selectedassurance-related procedures, including self-auditing routines, may beapplied to, the stakeholder matrix.

From any of the states 746-752, program flow may move to the end state718, terminating the session with the stakeholder-user. Alternately,program flow may return to the state 704 where the stakeholder-user mayselect another sub-mode of operation for the system 100 (FIG. 1A).

Assuming the stakeholder user selects the reporting sub-mode in thestate 704, program flow moves to a state 754. The reporting sub-mode isone embodiment of an interface by which a stakeholder-user may generatevarious outcome displays regarding the value creation or valuerealization performance of the business enterprise. This may include,for example, generating various value creation outcome displays,generating accounting outcome displays which comply with the variousaccounting standards of different countries or standards-establishingentities, or generating outcome displays in other generally-acceptedformats. Those skilled in the art will recognize that other outcomedisplay generation schemes may be contemplated. The generation ofoutcomes displays will be described in more detail below.

In the state 754, the stakeholder user may select a reporting template.For example, the reporting template may specify available types ofreport formats which may be generated by the system 100 (FIG. 1A). Fromthe state 754, program flow may move to a state 756. In the state 756,the user may select one of the four perspectives on the businessenterprise from which the user desires to generate a report. Then,program flow moves to a state 758 where the user may select a specificreporting format from among several available formats.

From the state 758, program flow may move to a state 760 where selectedoutcome displays may be generated from the formula matrix in thedatabase 104 (FIG. 1A). Alternately, if the user selects the eventmatrix, program flow may move to a state 762 where selected outcomedisplays may be generated from the event matrix in the database 104(FIG. 1A). Assuming the user selects the capacity matrix, program flowmay move to a state 764 where selected outcome displays may be generatedfrom the capacity matrix. If the user selects the stakeholder matrix,program flow may move to a state 766 where selected outcome displays maybe generated from the stakeholder matrix.

The foregoing has described operation of the system in value creationmode. A description of software architecture for operating in valuerealization mode to generate continuously updated outcome displayssimilar to those that might be generated by a traditionaltransaction-based accounting system follows below.

FIG. 23 is a block diagrammatic view of a software architecture 900 forenabling the system 100 (FIG. 1A) of the invention to operate in a valuerealization mode. The software architecture 900 may include a number ofsoftware modules 901-905, each of which controls the CPU 102 to performcertain functions, as explained herein. The event matrix module 901stores data with respect to future and past events. The object databasemodule 902 stores information about various data objects and therelationships among those data objects. The value realization reportselector module 903 enables a user to select among a number ofalternative value realization outcome displays that the system iscapable of generating. Based on the outcome displays selected by theuser, the event/objects filter module 904 in combination with thecalculation engine module 905 generates and displays the selectedoutcome displays. These modules will be described in more detail below.

FIG. 24 is a diagrammatic view of the event matrix module 901 of FIG. 23illustrating an example of certain event attributes that may be utilizedby the system while operating in value realization mode. Events in theevent matrix 901 may be classified, for example, as future events 906 a,and past events 906 b. For each event in the matrix 901, informationthat may be recorded in the matrix 901 may include date information ofinitial entry of information into the matrix 907 a, informationidentifying a user entering the information into the matrix 907 b, dateinformation of updating the information in the matrix 907 c, informationidentifying a user entering updated information into the matrix 907 d,assumption information 907 f, event type information 907 g, objectrelationship information 907 h, and other information relating to anevent record.

In FIG. 24 multiple event records are illustrated. For example, severalpast event records 906 b are recorded in the matrix 901. Past event99-4127 is illustrated as being entered into the matrix 901 on Jul. 2,1999 by Alice C. Since the event has already occurred, it is a knownorder event and involved an order of 100 units of Product A by CustomerA. Past event 99-4690 is illustrated as being entered into the matrix901 on Jul. 20, 1999. Since the event has already occurred, it is aknown manufacture event and involved the manufacture of 100 units ofProduct A. Past event 99-5201 is illustrated as being entered into thematrix 901 on Jul. 25, 1999 by John P. Since the event has alreadyoccurred, it is a known sale event and involved a sale of 100 units ofProduct A to Customer A. Past event 99-6374 is illustrated as beingentered into the matrix 901 on Aug. 20, 1999 by Alice C. Since the eventhas already occurred, it is a known payment event and involved a $5,000cash payment by Customer A for the purchased units. Accordingly, theevents for a particular stream of transactions can be recorded in theevent matrix 901.

The event matrix 901 also records future events 906 a, as shown in FIG.24. Future events 906 a can be affected and updated accordingly by knownevent occurrences. For example, as shown in FIG. 24, future event 99-0is illustrated as being entered into the matrix 901 on Jan. 1, 1999 asan assumed revenue event indicating 900,000 available units of ProductA. After an order of 100 units was recorded in the event matrix 901 asdescribed above, the future assumed revenue event 99-0001 is illustratedas being entered updating the event 99-0 information accordingly; inthis case, updating the amount of available units of Product A. Otherevent stream information may be similarly stored and updated in theevent matrix 901.

FIGS. 25A-C are respective diagrammatic views of object records that maybe stored in the above described object database module 902. FIG. 25A isa diagrammatic view of a customer object record 908 that may be storedin the object database 902. Exemplary record fields for the customerobject record 908 may include customer information, such as Name,Address, Contact information and other customer details, and eventrelationship identifiers that operate to dynamically link appropriateevents stored in the event matrix 901 with particular object recordsstored in the object database 902. For example, in FIG. 25A, thecustomer object record 908 is shown having appropriate dynamic eventidentifiers relating to the information pertaining to Customer A storedin the event matrix 901 described above with reference to FIG. 24.

FIG. 25B is a diagrammatic view of a product object record 909 that maybe stored in the object database 902. Exemplary record fields for theproduct object record 909 may include product information, such as name,components, price, cost, and other product details, and eventrelationship identifiers that operate to dynamically link appropriateevents stored in the event matrix 901 with particular object recordsstored in the object database 902. For example, in FIG. 25B, the productobject record 909 is shown having appropriate dynamic event identifiersrelating to the information pertaining to Product A stored in the eventmatrix 901 described above with reference to FIG. 24.

FIG. 25C is a diagrammatic view of a financial object record 910 thatmay be stored in the object database 902. Exemplary record fields forthe financial object record 910 may include cash information, such asbank name, address, contact information, and account number, and eventrelationship identifiers that operate to dynamically link appropriateevents stored in the event matrix 901 with particular object recordsstored in the object database 902. For example, in FIG. 25C, thefinancial object record 910 is shown having appropriate dynamic eventidentifiers relating to the information pertaining to payment eventsstored in the event matrix 901 described above with reference to FIG.24. Other object records can be created and the above are merelyexemplary.

FIG. 26 is a diagrammatic view illustrating interaction between theevent matrix module 901 and the object database module 902 shown in FIG.23 for generating value realization outcome displays in accordance withthe invention. This interaction can be illustrated by the followingexample. Assume that Company A manufactures Products A and B. Assumealso that Customer 1 is a customer of Company A. Consider the followingillustrative event stream as follows: (a) Customer 1 places an orderwith Company A for 100 units of Product A at $50 each; (b) Company Acompletes the manufacture of the 100 units of Product A that wereordered, at a unit cost of $25 each; (c) the 100 units of Product A areshipped to Customer 1, and an invoice is issued by Company A to Customer1 for $5,000; (d) Customer 1 remits payment to Company A in the amountof $5,000.

In describing how the value realization mode of the present inventionprocesses this event stream, it is useful to draw a contrast between thepresent invention and a traditional transaction-based accounting system.In such a traditional transaction-based accounting system, this eventstream would normally be represented by two transactions as follows:

On shipment of the goods, the following entry would be made in the booksof account:

Dr. Accounts receivable $5,000

Cr. Sales $5,000

Dr. Cost of goods sold $2,500

Cr. Inventory $2,500

On receipt of payment for the goods, the following entry would be madein the books of account:

Dr. Cash $5,000

Cr. Accounts receivable $5,000

By contrast, in the value realization mode of the present invention,this event stream may be recorded by modifying the relationships amongevents and objects in the event matrix 901 and object database 902. Forexample, assuming that in the current year (i.e., 1999), event A may beassigned an identification number 99-4127, event B may be assigned anidentification number 99-4690, event C may be assigned an identificationnumber 99-5201, and event D may be assigned the identification number99-6374. These events are illustrated as being recorded in the eventmatrix 901 shown in FIG. 24 and described above.

Accordingly, for example, upon the occurrence of event A (99-4127), thesystem 100 (FIG. 1A) may record the particular event details of event Ain the event matrix 901. The system 100 may also modify the attributesof the object record Customer A to include an event identifier referenceto event A in the event matrix 901, and may modify the attributes of theobject record Product A to include an event identifier reference toevent A in the event matrix 901. Similarly, upon the occurrence of eventB (99-4690), the system 100 (FIG. 1A) may modify the attributes of theobject record Product A to include an event identifier reference toevent B in the event matrix 901.

Upon the occurrence of event C (99-5201), the system 100 (FIG. 1A) maymodify the attributes of the object record Customer A to include anevent identifier reference to event C in the event matrix 901, and mayalso modify the attributes of the object record Product A to include anevent identifier to event C in the event matrix 901. Since in valuecreation mode the system 100 (FIG. 1A) may have recorded as a futureevent that Customer A would purchase a certain quantity of goods fromCompany A, upon the occurrence of that known event (the purchase of somegoods), the future event may be modified accordingly. Similarly, uponthe occurrence of event D (99-6374) the system 100 (FIG. 1A) may modifythe attributes of the object record Customer A to include an eventidentifier reference to event D in the event matrix 901, and may modifythe attributes of the financial object record Cash to include an eventidentifier reference to event D in the matrix 901.

Further assume that after event C, a user makes a request for a valuerealization outcome display from the system 100 (FIG. 1A). Among thealternative outcome display formats presented to the user by the valuerealization report selector 906 (FIG. 22) is an outcome display on thestatus of the object Accounts Receivable. Outcome display generation isdescribed in more detail below.

In a traditional transaction-based accounting system, a report on thestatus of accounts receivable would be generated by printing out theaccounts receivable subledger of the general ledger. In the valuerealization mode of the present invention, a report on the status ofaccounts receivable may be generated by applying an appropriateEvent/Objects filter 904 to the event matrix 901 and passing theappropriate information to a calculation engine 905 as shown in FIG. 27.

Thus, in accordance with the example given above, an event/objectsfilter module 904 may scan the customer record object attributes foreach customer and the associated event matrix 901, selecting past events(i.e., known results) from the event matrix 901, select event identifierreferences for sales and payment event types (other event types can beselected depending on the report desired), and pass the selected eventidentifier references (and their associated information) to thecalculation engine 905. The calculation engine 905 may, for eachcustomer object record, calculate the appropriate amounts related toeach particular event and determine an accounts receivable report. Theresulting outcome display may be presented to the user.

A similar procedure could be used to generate other value realizationoutcome displays, such as inventory status, sales summary, completefinancial statements, and virtually any other report that is generatedby a traditional transaction-based accounting system. For example,inventory status outcome displays can be generated by applying a filterthat selects product object records, and filters purchase, manufactureand sales events, passing the filtered records to the calculation engine905 for generating the value of the inventory. Similarly, a salessummary can be generated by applying a filter that selects customerobject records and filters sales events for a particular period, passingthe relevant information to the calculation engine 905 for generatingthe value of sales for the specific time period. Other outcome displaysmay be generated using a similar technique of filtering relevantinformation.

Complete financial statements as of specified time in accordance withgenerally-accepted accounting principles may be generated, for exampleby applying associated filters to summarize the various events andobject relationships that comprise the balance sheet and the incomestatement, and a calculation engine that incorporates within it therules and conventions embodied in GAAP as currently defined by therelevant authorities.

Note that the system 100 (FIG. 1A) can be configured such that anupdated version of any selected outcome display report can be createdwhenever an event takes place. That is, the process of applying theappropriate event/object filter and applying the calculation engine canbe made to be continuous, updating the result based on each new event.Consequently, the system 100 can therefore be described as capable ofproducing continuously updated value realization outcome displays.

An advantageous difference between the value realization mode of thepresent invention and a traditional transaction-based accounting systemis that in the present invention the relationships among events andobjects are a central focus of the system. In the event-based system 100(FIG. 1A) objects may include customers, products available for sale,financial objects, such as cash, etc. Objects such as these are ineffect constants; what changes is the relationships among them and theevents in the event matrix 901. As events take place, the systemredefines these relationships.

By contrast, in a traditional transaction-based accounting system, whatis central is the transactions as they are recorded in the variousjournals and subledgers. All processing is built around transactions,combining them in various ways.

The foregoing demonstrates that the same event-based system architecturecan be deployed in value creation mode to generate outcome displays thatprovide a forward-looking perspective on value creation performance of abusiness enterprise, and in value realization mode to provide ahistorical perspective on value realization performance of a businessenterprise. A traditional transaction-based accounting system, however,is only capable of generating outcome displays on historical valuerealization. Combining the capability to generate value creation andvalue realization information from a single system provides an importantbenefit to business enterprises.

FIG. 28 illustrates an example of an alternative scheme for generatingoutcome displays using an outcome display interface for formattingcustomized outcome displays based on choices made by a stakeholder-userusing the invention. As shown in FIG. 28, choices relating to reportingmode may be selected by a user. Choices available may include valuecreation mode 1001, value realization mode 1002, or alternativereporting mode 1003. If a stakeholder-user selects value creation mode1001, a user may select a reporting view that the stakeholder-userwishes to access 1004. Choices available to the stakeholder-user mayinclude value creation/value realization formula, value stream model,value creation capacity, or value creation for multiple stakeholders.Other choices may also be available and the above are merely exemplary.

The user may also select value stream reporting options 1005. Availablechoices may include viewing a single value stream, in which case theoptions may include each value stream in the system, or viewing thevalue streams aggregated by technology, geography, or organizationalunit. Other options may also be available and the above are merelyexemplary.

A user may also select stakeholder perspective reporting options 1006.Choices within stakeholder perspective include customer perspective,employee perspective, supplier/business partner perspective,community/society perspective, shareholder perspective, or otherstakeholder perspectives as may be available in the system.

A user may also select whether the system is operating in vision viewversus performance tracking view 1007. In the case of vision view, thestakeholder-user may be asked to select one or more scenarios from alist of future scenarios that are available for comparison. The systemmay calculate outcomes for the chosen scenarios as described herein. Inthe case of performance tracking view, the user may specify any datesfor generating a view. The system may calculate outcomes based on theevents occurring between those time periods as described herein.

A user may also select different assumptions that the shareholder-userwishes to access 1009. Choices include viewing outcomes reflecting theofficial management events and assumptions, viewing results reflectingthe changes to events and assumptions made by one or more specifiedusers, and viewing the changes to events and assumptions made by one ormore specified groups. Other selectable assumptions may also beavailable and the above are merely exemplary.

A user may also choose the level of detail that the stakeholder-userwishes to view. Choices may include a range of levels of detail betweenthe highest (Level 1) view (minimum detail) to the lowest (Level 5) view(maximum detail). Users may make any of the above selections byinteracting with the system 100, such as, for example, by selecting fromavailable choices using a touchscreen or other interactive displaydevice, or by selecting from available menus using an I/O device. Basedon all of the foregoing choices, the system 100 (FIG. 1A) may select themost appropriate event/assumption filter 904 from among all theavailable value creation mode filters. Additionally, the system 100(FIG. 1A) may select the most appropriate calculation engine 905 fromamong all of the available value creation mode calculation engines. Forexample, one of the calculation engines may contain the formula neededto generate a value stream model from a customer perspective. Theselected filter 904 and calculation engine 905 may then generate thedesired outcome display in accordance with the stakeholder-user choices,as described above. The outcome display reflects results based on allthe events in the system 100 that match the chosen filter. Furthermore,as long as the user wishes to continue viewing a particular outcomedisplay, the outcomes can be updated in real-time based on theoccurrence of any additional events that fall within the parametersestablished by the event/assumption filter.

If the stakeholder-user chooses value realization mode from thedifferent reporting modes, the user may select from different reportformats that the user wishes to access 1010. Report format choices mayinclude financial statements, financial outcome displays (which mayinclude a variety of reports relating to assets, liabilities, revenuesor expenses), shareholder value reports, or other value realizationrelated reports as are available in the system.

A user may also select organizational unit outcome displays 1011.Available organizational unit outcome displays may include viewingoutcome displays relevant to a particular department, business unit,division, other structure, or the overall corporation as a whole. Otherreports may also be available and the above are merely exemplary.

A user may also select different accounting standards to use for reportgeneration. Available standards may include that applicable to aparticular country—e.g., U.S. GAAP, Canadian GAAP, etc., or that usinginternational GAAP. Other standards may also be selected.

A user may also select time period criteria for reporting 1012. Thestakeholder-user may select from different dates to generate outcomedisplays. Another available selection relates to the level of detailthat the stakeholder-user wishes to view 1013. Choices may include arange of levels of detail between highest (Level 1) view (minimumdetail) to lowest (Level 5) detail (maximum detail). As described above,users may make any of the above selections by interacting with thesystem 100, such as, for example, by selecting from available choicesusing a touchscreen or other interactive display device, or by selectingfrom available menus using an I/O device. Based on all of the foregoingchoices, the system 100 may select the most appropriate event/objectfilter 904 from among all the available value realization mode filters.In addition, the system 100 may select the most appropriate calculationengine 905 from among all the available value realization modecalculation engines. For example, one of the calculation engines maycontain the formulae that are necessary for generating a traditionalaccounting financial statement. The selected filter 904 and calculationengine 905 may then be used to generate the outcome display inaccordance with the stakeholder-user choices. The outcome displayreflects results based on all the events in the system that match thechosen filter. Furthermore, as long as the user wishes to continueviewing a particular outcome display, the outcomes can be updated inreal-time based on the occurrence of any additional events that fallwithin the parameters established by the event/object filter.

If the stakeholder-user selects the alternative reporting mode, the usermay select a reporting format that the stakeholder-user wishes to access1015. Available choices may include a balanced scorecard report, areport in accordance with the guidelines of the global reportinginitiative, a report in accordance with the format developed by Skandia(called the Skandia Navigator), a management discussion and analysisreport (MD&A), or any other generally accepted reporting format which isavailable in the system.

The user may also select to generate a report for a particularorganizational unit 1016, such as reports relevant to a particulardepartment, business unit, division, other structure, or the overallcorporation as a whole. Another choice relates to time period 1017. Thestakeholder-user may select particular dates to generate outcomedisplays.

The user may also select the level of detail that the stakeholder-userwishes to view 1018. Available choices include a range of levels ofdetail between the highest (Level 1) view (minimum detail) and thelowest (Level 5) view (maximum detail). Users may make any of the aboveselections by interacting with the system 100, such as, for example, byselecting from available choices using a touchscreen or otherinteractive display device, or by selecting from available menus usingan I/O device. Based on all of the foregoing choices, the system 100(FIG. 1A) may select the most appropriate event/object filter 904 fromamong all of the available alternative reporting mode filters and mayselect the most appropriate calculation engine 905 from among all of theavailable alternative reporting calculation engines. For example, one ofthe calculation engines may contain the formulae that are necessary forgenerating a balanced scorecard report.

The selected filter 904 and calculation engine 905 may be used togenerate the outcome display in accordance with the stakeholder-userchoices. The outcome display reflects results based on all of the eventsin the system that match the chosen filter. Furthermore, as long as theuser wishes to continue viewing the particular outcome display, theoutcomes can be updated in real-time based on the occurrence of anyadditional events that fall within the parameters established by theevent/object filter as described herein.

FIG. 29 is a flow chart illustrating an exemplary method by which acustomized assurance report on an outcome display may be generated inreal time based on various automated procedures. Once a particularoutcome display has been generated as described above, astakeholder-user may make a choice as to whether the stakeholder-userwishes to view an assurance report (Step 1100). In some cases, they mayalso be able to choose among higher or lower levels of assurance.

Assuming a stakeholder-user chooses to view an assurance report, thesystem may perform a number of automated assurance procedures (Step1101) to generate an assurance report. For example, the system mayverify that the filter 904 and calculation engine 905 used to generatethe outcome display are the appropriately associated given thestakeholder-user's outcome display parameter selections. The system mayalso verify the mathematical accuracy of the calculations performed bythe calculation engine 905, and may verify that the outcome displayinformation properly reflects any authoritative standards, such as U.S.GAAP or the like. The system may also verify the integrity of theunderlying data in the database, through such procedures asevent-assumption-object relationship tests, which ensure that allobjects and assumptions are linked to events (and vice-versa),event-assumption-object consistency tests, which ensure that there areno inconsistencies between event-assumption or event-objectrelationships, assumptions limits tests, which ensure that allassumptions fall within limits established when they were firstestablished (i.e., a market share assumption would be set such that itcould not exceed 100%), outcome limits tests, which ensure that theoutcomes calculated by the system fall within reasonable limitsestablished during system installation, data validation tests, whichensure that all data in the system fall within specified parameters, andother tests as applicable.

To provide an assurance report on an outcome display, a number ofassurance procedures may be independently performed to verify theintegrity of the information provided in the outcome display (Step1102). This may be performed by an individual assurance provider, oralternatively, this functionality may be provided automatically in thesystem. Exemplary assurance procedures might consist of manual orautomatic tests performed at various times throughout a year to test theaccuracy of information in the company's database. In addition to thesetests, software may execute in parallel with that running on a clientcomputer network, allowing an assurance provider to perform a number ofparallel automated procedures (Step 1103), such as those describedabove.

Assuming the stakeholder-user has selected to view an assurance report,the report may be generated (Step 1104) by the parallel software runningon the assurance provider's network. Alternatively, the assurance reportmay be generated by the system itself. The assurance report may beassembled from a library of assurance report components in accordancewith decision rules established by the assurance provider, and whichwill be described in more detail below. For example, assurance reportcomponents may include records relating to the level of assurancedetail, records relating to the nature of the procedures performed, andrecords relating to the results of applying such procedures. Thedecision rules specify how the assurance report components areassembled. Assembly may be based on the choices made by thestakeholder-user in selecting the attributes of the outcome display theywish to review, the results of the automated assurance proceduresperformed by the client system, as noted above, the results of themanual assurance procedures previously undertaken by the assuranceprovider, the results of the parallel automated assurance proceduresperformed by the parallel system running on assurance provider'scomputer network, as noted above, as well as other alternatives.

Once the assurance report has been compiled it may be linked with theoutcome display by means of a hyperlink feature (Step 1105), or othersimilar associating principle. This aids to ensure that the assurancereport is provided independently to the stakeholder-user, and that thereis no opportunity of alteration of the assurance report by the client.

Provided a stakeholder-user continues to view a particular outcomedisplay on which the stakeholder-user has requested an assurance report,the above procedures may continue to be performed on an iterative basis(Step 1106) to ensure that the assurance report is updated to reflectthe results of additional events as they occur.

To more clearly illustrate the decision rules described above, assumethat a stakeholder-user makes the following outcome display selectionsto view a particular value creation outcome display, for example, usingthe interface described above with reference to FIG. 28. Assume thestakeholder-user selects a value stream model, electing to view valuestream A, from a shareholder's perspective, using performance trackingview for the past year, in accordance with management's officialassumptions, at maximum detail, and requests an assurance report. FIGS.30A and 30B illustrate exemplary assurance procedure decision rules thatmay be used to generate the assurance report for this example. Eachdecision rule may be associated with a first procedure (column 1200 a)to be performed if the rule is satisfied, and a second procedure (column1200 b) to be performed if the rule is not satisfied. In accordance withthese exemplary procedures, an assurance report can be generated for theoutcome display being viewed providing a detailed analysis of theassurance procedure decision rules and indicating where assurance faultscan be found in the generation of the outcome display information. Theprovided index of decision rules is complete enough to provide for allpossible combinations of choices that a user might make in selecting anoutcome display. Accordingly, the entire set of decision rules areavailable for assurance report processing; however, generally only thoserules that are relevant to the particular outcome display are used bythe system to generate the assurance report. This rule list is notexhaustive, and may be updated accordingly to include new rules or tochange existing rules. FIGS. 31A, 31B, and 31C illustrate exemplaryassurance report components that may be presented in an assurance reportrequested by a stakeholder-user. The reporting components 1202 maydepend on the results of the analysis performed using the assuranceprocedure decision rules described above. Accordingly, astakeholder-user can receive an assurance report relating to the outcomedisplay being viewed so as to more readily rely on the displayed data asbeing accurate assessments of value creation and/or value realization.

FIG. 32 is a flowchart illustrating a method for obtaining benchmarkinginformation in real-time through a network of benchmarking serviceproviders. As an example, referring to FIG. 32, Client A wishes toobtain benchmarking information. The invention enables an authorizedindividual (Client A) to specify the information it wishes to benchmark(Step 1300). Exemplary information may include key assumptions in itsvalue creation model that it wishes to compare with assumptions used byother companies, value creation or value realization outcomes in adefined area of its business operations compared with outcomes obtainedby competitors with similar operations, value creation capacity comparedwith value creation capacity in other companies, and value created orrealized for specific stakeholders compared with value created forsimilar stakeholders in comparable companies, or any other aspect ofenterprise performance.

Based on the choices made by the authorized individual at Client A, anelectronic benchmarking request may be generated by the system (Step1301) and forwarded to a designated benchmarking service provider (Step1302).

Upon receipt of the client request, specialized software at thebenchmarking service provider may automatically forward a request forrelevant benchmarking information to all of its clients who subscribe tothe benchmarking service (Step 1303). Additionally, upon receipt of theclient request, specialized software at the benchmarking serviceprovider may automatically forward a request for relevant benchmarkinginformation to all other benchmarking service providers in the network(Step 1304). Upon receipt of the request from the requestingbenchmarking service provider, specialized software at the otherbenchmarking service providers automatically forwards a request forrelevant benchmarking information to all of their clients who subscribeto the benchmarking service (Step 1305). Accordingly, a client wishingto obtain benchmarking information is able to obtain comparativeinformation from a larger number of comparable companies than is servedby a single benchmarking service provider.

Upon receipt of a request from a benchmarking service provider forbenchmarking information, a client system may automatically perform asearch for relevant comparable information and automaticallyelectronically forward this information to the requesting benchmarkingservice provider (Step 1306). Upon receiving the comparable informationfrom one or more clients, the target benchmarking service provider(s)may automatically aggregate the comparable information received from oneor more clients (Step 1307). The provider(s) may then electronicallyforward the aggregated information to the requesting benchmarkingservice provider (Step 1308).

Upon receiving the aggregated benchmarking information from the targetbenchmarking service providers, the requesting benchmarking serviceprovider aggregates the aggregated information received with thatreceived from its own clients (Step 1309) and forwards the resultingbenchmarking information to Client A (Step 1310). The above process maybe iteratively performed if a client wishes to access continuallyupdated benchmarking information.

Alternatively, benchmarking service providers may agree to continuouslypool and aggregate commonly requested benchmarking information in orderto speed the response time of the system to client requests. Where theclient request is for information that has been aggregated in this way,the request may be fulfilled from the continuously aggregatedinformation.

While the foregoing has been with reference to particular embodiments ofthe invention, it will be appreciated by those skilled in the art thatchanges in these embodiments may be made without departing from theprinciples and spirit of the invention, the scope of which is defined bythe appended claims.

What is claimed is:
 1. A computer implemented method for providingreal-time benchmarking information relating to the performance of abusiness enterprise, comprising: developing and storing in a memorydevice a data structure including information related to the performanceof a business enterprise; initiating a request, to a computerimplemented benchmarking system, for benchmarking information includingone or more benchmarking service providers, each of the benchmarkingservice providers having one or more associated clients, thebenchmarking service providers relaying the request for benchmarkinginformation to their clients, wherein the initiating step furthercomprises initiating a request for benchmarking information to a firstbenchmarking service provider, and relaying that request to the one ormore additional benchmarking service providers in the benchmarkingnetwork; responding, by the computer implemented benchmarking system, tothe request for benchmarking information by providing relevantbenchmarking information to the associated benchmarking serviceproviders; aggregating, by the computer implemented benchmarking system,the received benchmarking information to yield composite benchmarkinformation relating to the performance of the business entity, whereinthe aggregating step further comprises firstly aggregating by each ofthe associated benchmarking service providers the relevant benchmarkinginformation from each of the responding client systems, providing theaggregated benchmarking information to the first benchmarking serviceprovider, and secondly aggregating the aggregated benchmarkinginformation with the relevant benchmarking information provided to thefirst benchmarking service provider from its client systems; and whereinfor each notified client, the responding step further comprisessearching for relevant benchmarking information from associated datastructures and providing the relevant benchmarking information to theassociated benchmarking service providers.
 2. The method of claim 1,wherein the data structure includes information relating to the valuecreation performance of a business enterprise.
 3. The method of claim 1,wherein the data structure includes information relating to a valuerealization performance of a business enterprise.
 4. The method of claim1, wherein the data structure includes information relating to theperformance of a business enterprise as measured by generally acceptedalternative performance reporting formats.
 5. The method of claim 1,wherein the data structure includes a plurality of future and pastevents and related assumptions.
 6. The method of claim 5, wherein thebenchmarking request is repeatedly generated based on the occurrence ofone or more events.
 7. The method of claim 1, further comprisingproviding a composite benchmarking information to a requesting clientsystem.
 8. The method of claim 1, wherein the benchmarking informationrelates to value creation performance.
 9. The method of claim 1, whereinthe benchmarking information relates to value realization performance.10. The method of claim 1, wherein the benchmarking information iscontinuously pooled and updated and wherein the response to the requestincludes providing relevant benchmarking information from thecontinuously pooled information.